hash stringlengths 32 32 | doc_id stringlengths 7 13 | section stringlengths 3 121 | content stringlengths 0 2.2M |
|---|---|---|---|
3be34f7b3db0557b264c09436216ee4a | 103 902 | 3.3.3 B | BE Best Effort BME Bandwidth Management Entity BSA Basic Set of Applications BTP Basic Transport Protocol |
3be34f7b3db0557b264c09436216ee4a | 103 902 | 3.3.4 C | C2C-CC Car to Car Communication Consortium C2C-CC Car to Car Communication Consortium CA Certification Authority CAM Cooperative Awareness Message CAS Cooperative Awareness Service CBR Channel Busy Ratio CC Congestion Control CCAM Cooperative, Connected and Automated Mobility CCMS C-ITS Security Credential Management System ETSI ETSI TR 103 902 V2.1.1 (2026-01) 16 CDD Common Data Dictionary CDF Cumulative Distribution Function CEN Commission Européen de Normalization C-ITS Cooperative Intelligent Transportation Systems C-ITS-ECOS Cooperative Intelligent Transportation Systems Ecosystem C-ITS-S Cooperative ITS-Station CL Channel Load CP Collective Perception CPM Collective Perception Message CPS Collective Perception Service CSMA Carrier Sense Multiple Access CSP Communication Service Parameter CW Continues Wave |
3be34f7b3db0557b264c09436216ee4a | 103 902 | 3.3.5 D | DATEX Data Exchange DAZ Driver Awareness Zone DCC Decentralized Congestion Control DDP Device Data Provider DE Data Element DEN Decentralized Environmental Notification DENM Decentralized Environmental Notification Message DENS Decentralized Environmental Notification Service DF Data Frame DFRS Data For Road Safety DLC Data Link Layer DoS Denial of Service DPIA Data Protection Impact Assessment DSRC Dedicated Short Range Communication |
3be34f7b3db0557b264c09436216ee4a | 103 902 | 3.3.6 E | ECC Electronic Communications Committee ECO ECOlogical ECOS ECOSystem ECU Electronic Control Unit EEBL Electronic Emergency Break Light EG European Guide EIRP Effective Ideal Radiated Power EN European Norm ES European Standard EU European Union |
3be34f7b3db0557b264c09436216ee4a | 103 902 | 3.3.7 F | FAC FACility FL Facilities Layer FL-SDU Facilities Layer Service Data Unit FoV Field of View FuSa Functional Safety |
3be34f7b3db0557b264c09436216ee4a | 103 902 | 3.3.8 G | GBC GeoBroadCast GCBR Global Channel Busy Ratio GCRA Generic Cell Rate Algorithm GDPR General Data Protection Regulation GN GeoNetworking GNSS Global Navigation Satellite System ETSI ETSI TR 103 902 V2.1.1 (2026-01) 17 GPC GNSS Positioning Correction GPCH General Purpose CHannel GPRS General Packet Radio Service GR Group Report GS Group Specification |
3be34f7b3db0557b264c09436216ee4a | 103 902 | 3.3.9 H | H Header HDL Hardware Description Language HEN Harmonised European Norm HF High Frequency HMI Human Machine Interface HSM Hardware Security Modules |
3be34f7b3db0557b264c09436216ee4a | 103 902 | 3.3.10 I | I2V Infrastructure to Vehicle I2X Infrastructure to Everything ICT Information Communication Technology ID IDentifier IETF Internet Engineering Task Force IN INterface IP Internet Protocol IPv6 Internet Protocol version 6 IR Infra-Red incoherent light IS Infrastructure Services ISO International Standardization Organisation ITIS International Traveller Information Systems ITS Intelligent Transport Systems ITS-AID ITS-Application IDentifier ITS-C Intelligent Transportation Systems Constellation ITS-C Intelligent Transportation Systems Communications ITS-S Intelligent Transportation Systems Station ITU-T International Telecommunication Union - Telecommunication IVI Infrastructure to Vehicle Information IVIM Infrastructure to Vehicle Information Message IVN In-Vehicle Network |
3be34f7b3db0557b264c09436216ee4a | 103 902 | 3.3.11 J | Void. |
3be34f7b3db0557b264c09436216ee4a | 103 902 | 3.3.12 K | KAF Keep Alive Forwarding |
3be34f7b3db0557b264c09436216ee4a | 103 902 | 3.3.13 L | LCLR Local Channel Load Ratio LDM Local Dynamic Map LF Low Frequency LLC Logical Link Control layer LTE Long-Term Evolution ETSI ETSI TR 103 902 V2.1.1 (2026-01) 18 |
3be34f7b3db0557b264c09436216ee4a | 103 902 | 3.3.14 M | MAC Medium Access Control MAP Road topology MAPEM MAP (topology) Extended Message MCI MCO Control Information MCM Manoeuver Coordination Message MCS Manoeuver Coordination Service (type of message in ITS) MCS Modulation and Coding Scheme (technology term in radio communication) MDA Minimum Dissemination Area MHE Message Handling Entity MIM Marshalling Infrastructure Message MM Multi Model MSB Most Significant Bit MTU Maximum Transmit Unit MVM Marshalling Vehicle Message |
3be34f7b3db0557b264c09436216ee4a | 103 902 | 3.3.15 N | N&T Networking & Transport layer NAP National Access Point NAPCORE National Access Point Coordination Organisation for Europe NL Networking & transport Layer NR New Radio NWI New Work Item |
3be34f7b3db0557b264c09436216ee4a | 103 902 | 3.3.16 O | OID Object IDentifier OS Operating System OSI Open System Interconnection |
3be34f7b3db0557b264c09436216ee4a | 103 902 | 3.3.17 P | PA Parking Availability PAS Parking Availability Service PCI Protocol Control Information PDU Protocol Data Unit PHY PHYsical layer PI Parking Information PIM Parking Information Message PLCP Physical Layer Convergence Protocol POI Point Of Interest POIM Point Of Interest Message POIM-PA Point Of Interest Message - for Parking Availability PoTi Position and Time PRR Packet Reception Ratio PTW Power Two-Wheeler PVD Probe Vehicle Data |
3be34f7b3db0557b264c09436216ee4a | 103 902 | 3.3.18 Q | QAM Quadrature Amplitude Modulation QM Quality Management QoS Quality of Service QPSK Quadrature Phase Shift Keying ETSI ETSI TR 103 902 V2.1.1 (2026-01) 19 |
3be34f7b3db0557b264c09436216ee4a | 103 902 | 3.3.19 R | R Release R-ITS-S Roadside ITS Station RLT Road and Lane Topology RM Resource Management RRM Radio Resource Management RSE Road Side Equipment RSSI Received Signal-Strength Indicator RSU Roadside Unit RTCM Radio Technical Commission for Maritime services RTCMEM RTCM Extended Message RTK Real Time Kinematic RWW Roads Works Warning RZ Relevance Zone |
3be34f7b3db0557b264c09436216ee4a | 103 902 | 3.3.20 S | SA Service Announcement SAM Service Announcement Message SAS Service Announcement Service SCH Service CHannel SCI Security Control Information SCO Single Channel Operations SDO Standards Development Organisation SDU Service Data Unit SDV Slow Driving Vehicle SHA Secure Hash Algorithm SHB Single Hop Broadcast SIB Security Information Base SINR Signal to Noise Interference Ratio SL Service (Application) Layer SNMP Simple Network Management Protocol SOA Service-Oriented Architecture SOTIF Safety Of The Intended Functionality SP Service Provider SPATEM Signal Phase and Timing Extended Message SR Special Report SREM Signal Request Extended Message SRTI Safety Related Traffic Information SSEM Signal request Status Extended Message SSP Service Specific Permissions |
3be34f7b3db0557b264c09436216ee4a | 103 902 | 3.3.21 T | TB Technical Body TC ID Traffic Class IDentity TC Technical Committee TCC Traffic Control Centre TLC Traffic Light Control TLM Traffic Light Manoeuver TMC Traffic Management Centre TOGAF The Open Group Architecture Framework TPEG Transport Protocol Experts Group TR Technical Report TS Technical Specification TVRA Threat and Vulnerability Risk Assessment ETSI ETSI TR 103 902 V2.1.1 (2026-01) 20 |
3be34f7b3db0557b264c09436216ee4a | 103 902 | 3.3.22 U | UC Use Case UML Unified Modelling Language UMTS Universal Mobile Telecommunications System UPER Unaligned Packed Encoding Rule USB Universal Serial Bus |
3be34f7b3db0557b264c09436216ee4a | 103 902 | 3.3.23 V | V2I Vehicle to Infrastructure V2N Vehicle to Network V2N2X Vehicle to Network to Everything V2V Vehicle to Vehicle V2X Vehicle to Everything VAM VRU Awareness Message VBS VRU Basic Service V-ITS-S Vehicular and personal ITS Station VoI Value of Information VRU Vulnerable Road User |
3be34f7b3db0557b264c09436216ee4a | 103 902 | 3.3.24 W | WGX Working Group X (where X is a number) |
3be34f7b3db0557b264c09436216ee4a | 103 902 | 3.3.25 X | X2X Everything to Everything X2N2X Anything to Network to Anything |
3be34f7b3db0557b264c09436216ee4a | 103 902 | 3.3.26 Y - Z | Void. ETSI ETSI TR 103 902 V2.1.1 (2026-01) 21 History Version Date Status V2.1.1 January 2026 Publication |
7470f1226238696862acc2f2b74c08a3 | 103 858 | 1 Scope | The present document is a Framework (Guide) to Implementing Autonomic/Autonomous IPv6 based 5G Networks, by leveraging the ETSI GANA Multi-Layer AI / Multi-Layer Autonomic Management and Control Model and IPv6 Capabilities & Extensions that enable to Build Autonomic Networks. The Framework prescribes how to introduce software components called Autonomic Functions (ETSI GANA Decision-making-Elements (DEs)), e.g. Autonomic- QoS-Management-DE, Autonomic-Security-Management-DE, etc. in the 5G Architecture and its associated Management and Control Architecture. The DEs and their associated Algorithms (including analytics, optimization and AI algorithms) are meant to drive control-loops within Network Functions of the 5G network infrastructure and/or drive control-loops at the higher level of abstraction for self-management functionality that is positioned within the outer Management and Control realm of a 5G Network Infrastructure - within a platform called the GANA Knowledge Plane (KP) Platform. The Framework also serves to: • prescribe how to leverage certain IPv6 Capabilities in enabling Autonomic Functions (called Decision-making-Elements (DEs) in the present document) of the Autonomic 5G network to auto-discover each other, auto-discover various context information, monitoring data, and to exchange DE-to-DE control messages among each other for their collaborative operations in the Self-Driving/Self-Management Operations of the 5G network(s); • provide Guidance to Innovators of DEs and their associated Autonomics Algorithms, on the types of GANA DEs that should be designed to auto-configure and dynamically (autonomically) orchestrate and (re)-configure various IPv6 Protocols of the of 5G Network as driven by Service or Slice provisioning, or adaptively to meet certain objectives. |
7470f1226238696862acc2f2b74c08a3 | 103 858 | 2 References | |
7470f1226238696862acc2f2b74c08a3 | 103 858 | 2.1 Normative references | Normative references are not applicable in the present document. |
7470f1226238696862acc2f2b74c08a3 | 103 858 | 2.2 Informative references | References are either specific (identified by date of publication and/or edition number or version number) or non-specific. For specific references, only the cited version applies. For non-specific references, the latest version of the referenced document (including any amendments) applies. NOTE: While any hyperlinks included in this clause were valid at the time of publication, ETSI cannot guarantee their long-term validity. The following referenced documents may be useful in implementing an ETSI deliverable or add to the reader's understanding, but are not required for conformance to the present document. [i.1] ETSI White Paper No.16: "GANA - Generic Autonomic Networking Architecture - Reference Model for Autonomic Networking, Cognitive Networking and Self-Management of Networks and Services". [i.2] ETSI TS 103 195-2 (V1.1.1): "Autonomic network engineering for the self-managing Future Internet (AFI); Generic Autonomic Network Architecture; Part 2: An Architectural Reference Model for Autonomic Networking, Cognitive Networking and Self-Management". [i.3] White Paper No.1 of the ETSI 5G PoC: "C-SON Evolution for 5G, Hybrid SON Mappings to the ETSI GANA Model, and achieving E2E Autonomic (Closed-Loop) Service Assurance for 5G Network Slices by Cross-Domain Federated GANA Knowledge Planes". [i.4] ETSI TR 103 473 (V1.1.2): "Evolution of management towards Autonomic Future Internet (AFI); Autonomicity and Self-Management in the Broadband Forum (BBF) Architectures". ETSI ETSI TR 103 858 V1.1.1 (2026-03) 9 [i.5] ETSI TR 103 404: "Network Technologies (NTECH); Autonomic network engineering for the self-managing Future Internet (AFI); Autonomicity and Self-Management in the Backhaul and Core network parts of the 3GPP Architecture". [i.6] White Paper No.3 of the ETSI 5G PoC: "Programmable Traffic Monitoring Fabrics that enable On-Demand Monitoring and Feeding of Knowledge into the ETSI GANA Knowledge Plane for Autonomic Service Assurance of 5G Network Slices; and Orchestrated Service Monitoring in NFV/Clouds". [i.7] White Paper No.2 of the ETSI 5G PoC: "ONAP Mappings to the ETSI GANA Model; Using ONAP Components to Implement GANA Knowledge Planes and Advancing ONAP for Implementing ETSI GANA Standard's Requirements; and C-SON - ONAP Architecture". [i.8] ETSI TS 129 520 (V16.6.0): "5G; 5G System; Network Data Analytics Services; Stage 3 (3GPP TS 29.520 version 16.6.0 Release 16)". [i.9] ETSI TS 128 533 (V15.0.0): "5G; Management and orchestration; Architecture framework (3GPP TS 28.533 version 15.0.0 Release 15)". [i.10] NGMN Alliance: "5G End-to-End Architecture Framework v3.0.8". [i.11] White Paper No.4 of the ETSI 5G PoC: "ETSI GANA as Multi-Layer Artificial Intelligence (AI) Framework for Implementing AI Models for Autonomic Management & Control (AMC) of Networks and Services; and Intent-Based Networking (IBN) via GANA Knowledge Planes (KPs)". [i.12] ETSI GS AFI 002 (V1.1.1): "Autonomic network engineering for the self-managing Future Internet (AFI); Generic Autonomic Network Architecture (An Architectural Reference Model for Autonomic Networking, Cognitive Networking and Self-Management)". [i.13] ETSI TR 103 495: "Network Technologies (NTECH); Autonomic network engineering for the self-managing Future Internet (AFI); Autonomicity and Self-Management in Wireless Ad-hoc/Mesh Networks: Autonomicity-enabled Ad-hoc and Mesh Network Architectures". [i.14] Ranganai Chaparadza, Michal Wodczak, Tayeb Ben Meriem, Paolo De Lutiis, Nikolay Tcholtchev, Laurent Ciavaglia: "Standardization of resilience & survivability, and autonomic fault-management, in evolving and future networks: An ongoing initiative recently launched in ETSI", In proceedings of 2013 9th International Conference on the Design of Reliable Communication Networks (DRCN 2013), ISBN 9781479900497, 4-7 March 2013, Budapest, Hungary. [i.15] IETF RFC 9386: "IPv6 Deployment Status". [i.16] Reliance Jio: "IPv6-only adoption challenges and standardization requirements", 2020. [i.17] T-Mobile US: "Going IPv6-only", 2018. [i.18] Carl A. Sunshine: "Source Routing In Computer Networks", ACM SIGCOMM Computer Communication Review Volume 7, Issue 1, January 1977, pp. 29–33. [i.19] IETF RFC 8754: "IPv6 Segment Routing Header (SRH)", March 2020. [i.20] IETF RFC 8986: "Segment Routing over IPv6 (SRv6) Network Programming", February 2021. [i.21] ETSI GR IPE 001 (V1.1.1) (2021-08): "IPv6 Enhanced Innovation (IPE); Gap Analysis". [i.22] ETSI TS 123 501 (V16.6.0) (2020-10): "5G; System architecture for the 5G System (5GS) (3GPP TS 23.501 version 16.6.0 Release 16)". [i.23] IETF RFC 5120: "M-ISIS: Multi Topology (MT) Routing in Intermediate System to Intermediate Systems (IS-ISs)", February 2008. [i.24] IETF RFC 4915: "Multi-Topology (MT) Routing in OSPF", June 2007. [i.25] IETF draft-ietf-teas-ietf-network-slices: "A Framework for IETF Network Slices", January 2023 (work in progress). ETSI ETSI TR 103 858 V1.1.1 (2026-03) 10 [i.26] IETF RFC 9350: "IGP Flexible Algorithm", February 2023. [i.27] IETF RFC 9256: "Segment Routing Policy Architecture", July 2022. [i.28] IETF RFC 5440: "Path Computation Element (PCE) Communication Protocol (PCEP)", March 2009. [i.29] ETSI White Paper No. 16: "GANA - Generic Autonomic Networking Architecture". [i.30] IETF RFC 9313: "Pros and Cons of IPv6 Transition Technologies for IPv4-as-a-Service (IPv4aaS)", October 2022. [i.31] IETF RFC 6146: "Stateful NAT64: Network Address and Protocol Translation from IPv6 Clients to IPv4 Servers", April 2011. [i.32] IETF RFC 6147: "DNS64: DNS Extensions for Network Address Translation from IPv6 Clients to IPv4 Servers", April 2011. [i.33] IETF RFC 6877: "464XLAT: Combination of Stateful and Stateless Translation", April 2013. [i.34] IETF RFC 6333: "Dual-Stack Lite Broadband Deployments Following IPv4 Exhaustion", August 2011. [i.35] ETSI TS 103 878: "Core Network and Interoperability Testing (INT); Network Interoperability Test Description for IPv6-only services over 5G". [i.36] ETSI GR IP6 010: "IPv6-based SDN and NFV; Deployment of IPv6-based SDN and NFV". [i.37] IETF RFC 9341: "Alternate-Marking Method", December 2022. [i.38] IETF RFC 9342: "Clustered Alternate-Marking Method", December 2022. [i.39] IETF RFC 6241: "Network Configuration Protocol (NETCONF)", June 2011. [i.40] IETF RFC 7752: "North-Bound Distribution of Link-State and Traffic Engineering (TE) Information Using BGP", March 2016. [i.41] IETF RFC 8571: "IGP Traffic Engineering Performance Metric Extensions", March 2019. [i.42] IETF draft-ietf-idr-segment-routing-te-policy: "Advertising Segment Routing Policies in BGP", July 2022 (work in progress). [i.43] R. Chaparadza, S. Papavassiliou, S. Soulhi and J. Ding: "The Self-Managing Future Internet powered by the current IPv6 and extensions to IPv6 towards "IPv6++" — A viable roadmap Scenario for the Internet Evolution Path", 2010 IEEE™ Globecom Workshops, 2010, pp. 551-556, doi: 10.1109/GLOCOMW.2010.5700381. [i.44] Chaparadza, R., Petre, R., Prakash, A., Németh, F., Kukliński, S., Starschenko, A. (2011): "IPv6 and Extended IPv6 (IPv6++) Features That Enable Autonomic Network Setup and Operation", In: Szabó, R., Zhu, H., Imre, S., Chaparadza, R. (eds) Access Networks. AccessNets 2010. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol. 63. Springer, Berlin, Heidelberg. [i.45] A. Starschenko, N. Tcholtchev, A. Prakash, I. Schieferdecker and R. Chaparadza: "Auto-configuration of OSPFv3 routing in fixed IPv6 networks", 2015 7th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT), 2015, pp. 196-205, doi: 10.1109/ICUMT.2015.7382427. [i.46] Ranganai Chaparadza, Tayeb Ben Meriem, Benoit Radier, Szymon Szott, Michal Wódczak, Arun Prakash, Jianguo Ding, Said Soulhi, Andrej Mihailovic: "Implementation Guide for the ETSI AFI GANA model: A Standardized Reference Model for Autonomic Networking, Cognitive Networking and Self-Management", 2013 IEEE™ Globecom Workshops (GC Wkshps), 2013, pp. 935-940, doi: 10.1109/GLOCOMW.2013.6825110. ETSI ETSI TR 103 858 V1.1.1 (2026-03) 11 [i.47] N. Tcholtchev, A. Prakash, I. Schieferdecker, R. Chaparadza and R. Petre: "Auto-Collaboration for optimal network resource utilization in fixed IPv6 networks", 2012 IEEE™ Globecom Workshops, 2012, pp. 807-812, doi: 10.1109/GLOCOMW.2012.6477679. [i.48] Kaldanis, V., Benko, P., Asztalos, D., Simon, C., Chaparadza, R., Katsaros, G. (2011): "Methodology towards Integrating Scenarios and Testbeds for Demonstrating Autonomic/Self- managing Networks and Behaviors Required in Future Networks", In: Szabó, R., Zhu, H., Imre, S., Chaparadza, R. (eds) Access Networks. AccessNets 2010. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 63. Springer, Berlin, Heidelberg. [i.49] Prakash, A., Starschenko, A., Chaparadza, R. (2011): "Auto-discovery and Auto-configuration of Routers in an Autonomic Network", In: Szabó, R., Zhu, H., Imre, S., Chaparadza, R. (eds) Access Networks. AccessNets 2010. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol. 63. Springer, Berlin, Heidelberg. [i.50] Rétvári, G., Németh, F., Chaparadza, R., Szabó, R. (2009): "OSPF for Implementing Self-adaptive Routing in Autonomic Networks: A Case Study", In: Strassner, J.C., Ghamri-Doudane, Y.M. (eds) Modelling Autonomic Communications Environments. MACE 2009. Lecture Notes in Computer Science, vol. 5844. Springer, Berlin, Heidelberg. [i.51] Zafeiropoulos, A., Liakopoulos, A., Davy, A., Chaparadza, R. (2010): "Monitoring within an Autonomic Network: A GANA Based Network Monitoring Framework", In: Dan, A., Gittler, F., Toumani, F. (eds) Service-Oriented Computing. ICSOC/ServiceWave 2009 Workshops. ServiceWave ICSOC 2009 2009. Lecture Notes in Computer Science, vol. 6275. Springer, Berlin, Heidelberg. [i.52] Szymon Szott, Janusz Gozdecki, Katarzyna Kosek-Szott, Krzysztof Loziak, Marek Natkaniec, Michal Wagrowski, Ranganai Chaparadza: "Enabling autonomicity in wireless mesh networks with the ETSI AFI GANA reference model", International Journal of Network Management, First published: 01 August 2017. [i.53] "Evolution of the current IPv6 towards IPv6++ (IPv6 with Autonomic Flavours", In: International Engineering Consortium (IEC) Annual Review of Communications, vol. 60 (December 2008). [i.54] Georgios Aristomenopoulos, Timotheos Kastrinogiannis, Zhaojun Li & Symeon Papavassiliou: "An Autonomic QoS-centric Architecture for Integrated Heterogeneous Wireless Networks", Mobile Netw Appl 16, 490–504 (2011). [i.55] G. Aristomenopoulos, T. Kastrinogiannis, Z. Li, M. Wilson, M. González Juan, A. Lozano-López Jose, Y. Li, V. Kaldanis, S. Papavassiliou: "Autonomic mobility and resource management over an integrated wireless environment — A GANA oriented architecture", 2010 IEEE™ Globecom Workshops, Miami, FL, USA, 2010, pp. 545-550, doi: 10.1109/GLOCOMW.2010.5700379. [i.56] Z. Li: "An autonomic hierarchical mobility management framework for 3GPP heterogeneous networks", 2010 Future Network & Mobile Summit, Florence, Italy, 2010, pp. 1-8. [i.57] A. Jaron, P. Pangalos, A. Mihailovic, A.H. Aghvami: "Proactive autonomic load uniformisation with mobility management for wireless Internet Protocol (IP) access networks", Source: Volume 1, Issue 4, December 2012, p. 229 - 238: doi: 10.1049/iet-net.2011.0009, Print ISSN 2047-4954, Online ISSN 2047-4962. [i.58] A. Liakopoulos, A. Zafeiropoulos, C. Marinos, M. Grammatikou, N. Tcholtchev and P. Gouvas: "Applying distributed monitoring techniques in autonomic networks", 2010 IEEE™ Globecom Workshops, Miami, FL, USA, 2010, pp. 498-502, doi: 10.1109/GLOCOMW.2010.5700369. [i.59] European Commission (EC) funded FP7: "Exposing the Features in IP version Six protocols that can be exploited/extended for the purposes of designing/building Autonomic Networks and Services". [i.60] IETF draft-chaparadza-6man-igcp-00: "IETF Autonomic Networking Integrated Model and Approach (anima)". [i.61] IETF draft-chaparadza-6man-igcp-00.txt: "ICMPv6 based Generic Control Protocol (IGCP)". ETSI ETSI TR 103 858 V1.1.1 (2026-03) 12 [i.62] European Commission funded -EFIPSANS-FP7-IP Project: Deliverable-D3.2: "Advanced Network Services in Autonomic IPv6 Networking: Performance Analysis and Evaluation", issued on 31.12.2009 (accessed November 2023). [i.63] ETSI TR 103 747 (V1.1.1): "Core Network and Interoperability Testing (INT/WG AFI); Federated GANA Knowledge Planes (KPs) for Multi-Domain Autonomic Management & Control (AMC) of Slices in the NGMN® 5G End-to-End Architecture Framework". [i.64] EANTC: "MPLS SDN Interoperability Test 2023", SRv6 test. [i.65] ETSI GR IPE 005 (V1.1.1): "IPv6 Enhanced Innovation (IPE); 5G Transport over IPv6 and SRv6". [i.66] ETSI TR 103 626: "Autonomic network engineering for the self-managing Future Internet (AFI); An Instantiation and Implementation of the Generic Autonomic Network Architecture (GANA) Model onto Heterogeneous Wireless Access Technologies using Cognitive Algorithms". [i.67] ETSI White Paper No. 35: "IPv6 Best Practices, Benefits, Transition Challenges and the Way Forward", First edition, August 2020. [i.68] oneM2M TR-436: "Access & Home Network OAM Automation/Intelligence", Issue: 1 Issue Date: February 2021. [i.69] IETF RFC 8992 (2021): "Autonomic IPv6 Edge Prefix Management in Large-Scale Networks". [i.70] IETF RFC 8990: "GeneRic Autonomic Signalling Protocol (GRASP)". [i.71] Recommendation ITU-T Y.3324: "Requirements and architectural framework for autonomic management and control of IMT-2020 networks". [i.72] IETF RFC 7596: "Lightweight 4over6: An Extension to the Dual-Stack Lite Architecture". [i.73] IETF RFC 7599: "Mapping of Address and Port using Translation (MAP-T)". [i.74] IETF RFC 7597: "Mapping of Address and Port with Encapsulation (MAP-E)". |
7470f1226238696862acc2f2b74c08a3 | 103 858 | 3 Definition of terms, symbols and abbreviations | |
7470f1226238696862acc2f2b74c08a3 | 103 858 | 3.1 Terms | Void. |
7470f1226238696862acc2f2b74c08a3 | 103 858 | 3.2 Symbols | Void. |
7470f1226238696862acc2f2b74c08a3 | 103 858 | 3.3 Abbreviations | For the purposes of the present document, the following abbreviations apply: 3GPP 3rd Generation Partnership Project 5G SA 5G StandAlone AcN Autonomic Network AFI Autonomic Future Internet AFTR Address Family Transition Router AGG AGgregation Gateway AI Artificial Intelligence AMC Autonomic Management & Control AMF Access and Mobility Management Function AN Autonomous Network ETSI ETSI TR 103 858 V1.1.1 (2026-03) 13 ANIMA Autonomic Networking Integrated Model and Approach API Application Programming Interfaces APN Application - aware Networking APN6 Application - aware IPv6 Networking AS Autonomous System ASN Autonomous System Number ATS Abstract Test Suite BBF BroadBand Forum BFD Bidirectional Forwarding Detection BGP Border Gateway Protocol BGP-LS Border Gateway Protocol Link-State CAPEX CAPital EXpenditure CLAT Client-side NAT CLI Command Line Interface CPE Customer Premises Equipment CSG1 Communication Systems Group C-SON Centralized Self Organizing Network DC Data Centre DE Decision making Element DL DownLink DNS Domain Name System DS-lite Dual Stack lite D-SON Distributed - Self Organizing Network E2E End-to-End EC European Community ECMP Equal-Cost Multi-Path EMS Element Management System EPC Evolved Packet Core FBB Fixed BroaBand FlexE Flexible Ethernet FP7 Seventh Framework Programme FW FireWall GANA Generic Autonomic Network Architecture GRASP GeneRic Autonomic Signalling Protocol IANA Internet Assigned Numbers Authority ICMP Internet Control Message Protocol ICT Information and Communications Technology IFIT In-situ Flow Information Telemetry IGCP ICMPv6 based Generic Control Protocol IGP Interior Gateway Protocol IKE Internet Key Exchange IMS IP Multimedia Subsystem IoT Internet of Thing IP Internet Protocol IPE IPv6 Enhanced innovation IS-IS Intermediate System-to-Intermediate System ISP Internet Service Provider KP Knowledge Plane KP DE Knowledge Plane Decision-making Element KPI Key Performance Indicator MANO Management and Orchestration MAP-E Mapping of Address and Port with Encapsulation MAPE-K Monitor-Analyse-Plan-Execute over a shared Knowledge MAP-T Mapping of Address and Port using Translation MBB Mobile BoradBand MBTS Model-Based Translation Service MDAS Management Data Analytics Service ME Managed Entity MEC Mobile Edge Computing ML Machine Learning mMTC massive Machine Type Communications MPLS MultiProtocol Label Switching ETSI ETSI TR 103 858 V1.1.1 (2026-03) 14 NAT Network Address Translation NB NorthBound NE Network Element NF Network Function NFV Network Function Virtualisation NGMN Next Generation Mobile Networks NSSF Network Slice Selection Function NWDAF NetWork Data Analytics Function NWDAS NetWork Data Analytic Service OAM Operations Administration and Maintenance ODA Open Digital Architecture ONIX Overlay Network for Information eXchange OPEX OPerating EXpenses O-RAN Open RAN OSe Operating System embedded OSPF Open Shortest Path First OSS Operations Support Systems PE Provider Edge PLAT Provider-side NAT PoC Proof of Concept Pre-AGG Pre-Aggregation Gateway QoE Quality of Experience QoS Quality of Service RAN Radio Access Network RAN Radio Access Network RIC RAN Intelligent Controllers RR Route Reflectors SBA Service Based Architecture SDN Software Defined Networks SDO Standards Development Organizations SDWAN Software-Defined Wide Area Network SEG Secure Gateway SID Segment Identifier SLA Service Level Agreement SMF Session Management Function SNMP Simple Network Management Protocol SON Self Organizing Networks SPAN Switched Port Analyser SPF Shortest Path First SR-BE Segment Routing Best Effort SRH Segment Routing Header SR-PCE Segment Routing - Path Computation Engine SR-TE Segment Routing - Traffic Engineering TAP Test Access Points TE Traffic Engineering TLV Type-Length-Value TWAMP Two-Way Active Measurement Protocol UE User Equipment UPF User Plane Function URLLC Ultra Reliable and Low Latency Communications VNF Virtual Network Function VRF Virtual Routing and Forwarding WAN Wide Area Network WG Working Group YANG Yet Another Next Generation ETSI ETSI TR 103 858 V1.1.1 (2026-03) 15 4 Principles for Autonomic Networking and Autonomic Management & Control (AMC), and Enablers This clause refers to clause 4 of ETSI TR 103 747 [i.63]. The Generic Autonomic Networking Architecture (GANA) Reference Model serves as a standardized architectural framework for autonomic networking, cognitive networking, and self-management of networks and services. It defines a hierarchy of Functional Blocks (FBs) that implements a control-loop as the core driver of the self-management, their reference points, and messaging protocols, supporting both micro-level (within network elements) and macro-level (network-wide) autonomic control loops. Central to GANA is the Knowledge Plane (KP), which orchestrates intelligent management and control through key components such as network-level Decision-making Elements (DEs), the ONIX overlay for distributed information exchange, and the Model-Based Translation Service (MBTS) for protocol-agnostic communication between DEs and network elements. GANA's hybrid approach allows implementers flexibility in deploying autonomic logic either centrally (macro-autonomics) or in a distributed manner (micro-autonomics), and is compatible with hybrid Self- Organizing Networks (SON) models. GANA DEs are organized hierarchically to enable scalable and coordinated autonomic management. Higher-level DEs, often situated within the Knowledge Plane (KP), exercise supervisory control over lower-level DEs and Managed Entities (MEs) by implementing intent-driven, closed control loops. Specifically, a higher-level DE analyses aggregated network-wide data and determines the appropriate intent or configurations. It then communicates directives, intent/policies, or configuration parameters to subordinate DEs, which are instantiated within specific network elements or functions. These lower-level DEs, in turn, execute fast, localized control loops—directly managing the behavior and state of their respective MEs based on the guidance received from the higher-level DE. This hierarchical control structure ensures that overarching network objectives are maintained, while allowing for rapid, context-aware adjustments at the local level. The approach enables seamless coordination between macro-level (network-wide) and micro-level (element-specific) autonomics, promoting both global optimization and local agility in network management. GANA facilitates integration with diverse management and control systems as depicted in Figure 1 with NorthBound (NB) Application Programming Interfaces (API) (e.g. SDN controllers, OSS/BSS, NFV MANO), leveraging standardized APIs to enable end-to-end orchestration and analytics. GANA also addresses the coordination and collaboration among autonomic functions, the handling of intent-based networking, and the design principles necessary for the stability and synchronization of control loops, positioning itself as a holistic and unifying framework for autonomic management and control. ETSI ETSI TR 103 858 V1.1.1 (2026-03) 16 Figure 1: GANA Knowledge Plane (KP) interfaces with multiple management and control systems, as well as integrates with various event, data, and knowledge sources, thereby enabling selective and dynamic network programmability 5 Use Cases for AI/ML and Autonomics in E2E IPv6 based 5G Networks in general; and Mappings to GANA DEs that help implement particular Use Case 5.1 Autonomic Management and Control (AMC) of Network Slices ETSI TR 103 747 [i.63] and clause 6.6 of the present document discuss Autonomic Orchestration and Service and Security Assurance of E2E 5G Network Slices. Autonomic orchestration and use of SRv6 can be performed by a GANA Knowledge Plane (KP) for the Transport Network to dynamically create transport network slices based on SRv6 and perform service and security assurance of the transport network slices. Clause 6.6 also provides insights on autonomics with use of SRv6. ETSI ETSI TR 103 858 V1.1.1 (2026-03) 17 5.2 Auto-Discovery and Auto-Configuration (Self-Configuration) Use Case This is an Autonomics Use Case by which GANA NODE_LEVEL_AC_DE provides logic, algorithms to ensure plug and play mechanisms of GANA Node. Provide auto discovery mechanisms and auto configuration mechanisms. The NODE_LEVEL_AC_DE may self-adapt the GANA Node according to GANA Profile derived from the KP's Network Level_AC_DE and orchestrate the different DEs within the GANA Node and in collaboration with other DEs outside the GANA node. The Use Case also includes the aspect by which GANA NETWORK_LEVEL_AC_DE provides logic, algorithm(s) to ensure plug and play mechanisms of GANA Network. Provide auto discovery, bootstrapping mechanisms and auto configuration mechanisms. The NETWORK_LEVEL_AC_DE may self-adapt the GANA Network according to GANA profile defined by an administrator domain and orchestrate the different DEs within the GANA network and in collaboration with other administrative domains. NOTE 1: ETSI TS 103 195-2 [i.2] provides more details of these two DEs, guidance on how to design their associated Control-Loops, and how they complement and interwork with other when both are implemented for the targeted network architecture and its associated management and control architecture. NOTE 2: There already exists in literature some research and implementation and validation work published on such autonomics use case, some of which are based on the GANA framework and IPv6. For example, readers may find work in [i.44], [i.49], [i.45], [i.48], [i.49], [i.1] and [i.62] very useful in this regard. |
7470f1226238696862acc2f2b74c08a3 | 103 858 | 5.3 Autonomic Mobility Management and Control Use Case | This is an Autonomics Use Case by which GANA FUNC_LEVEL_MOM_DE provides logic, algorithm(s) to manage mobility related MEs hosted by NE, for example, MEs that help drive handover or handoff of devices/nodes between different networks and technologies and also ensure service continuity of applications flows. The Use Case also includes the aspect by which the GANA NET_LEVEL_MOM_DE provides logic and algorithms to ensure handover between access networks, network element with service continuity. NOTE 1: ETSI TS 103 195-2 [i.2] provides more details of these two DEs, guidance on how to design their associated Control-Loops, and how they complement and interwork with other when both are implemented for the targeted network architecture and its associated management and control architecture. NOTE 2: There already exists in literature some research and implementation and validation work published on such autonomics use case, some of which are based on the GANA framework and IPv6 (e.g. IP Level Mobility Management with PMIPv6, etc.). For example, readers may find work in [i.48], [i.52], [i.55], [i.56], [i.57], [i.1] and [i.62] very useful in this regard. |
7470f1226238696862acc2f2b74c08a3 | 103 858 | 5.4 Autonomic Routing Management and Control Use Case | This is an Autonomics Use Case by which the GANA FUNC_LEVEL_RM_DE provides logic, algorithms to ensure the optimal and resilient routing of packets in the network in order to optimize the network utilization. The Use Case also includes the aspect by which the GANA NET_LEVEL_RM_DE provides logic, algorithms to ensure optimized routing of packets and flows in the network and in respect of network operator policies and in order to optimize the network's traffic routing objectives and behaviours. NOTE 1: ETSI TS 103 195-2 [i.2] provides more details of these two DEs, guidance on how to design their associated Control-Loops, and how they complement and interwork with other when both are implemented for the targeted network architecture and its associated management and control architecture. NOTE 2: Figure A.3 presents an illustration of the interworking and complementarity between the two DEs (more details on this are described in ETSI White Paper No.16 [i.1]). NOTE 3: There already exists in literature some research and implementation and validation work published on such autonomics use case, some of which are based on the GANA framework and IPv6. For example, readers may find work in [i.1], [i.50], [i.48] and [i.62] very useful in this regard. ETSI ETSI TR 103 858 V1.1.1 (2026-03) 18 |
7470f1226238696862acc2f2b74c08a3 | 103 858 | 5.5 Autonomic Forwarding Management Use Case | This is an Autonomics Use Case by which GANA FUNC_LEVEL_FWD_DE provides logic, algorithm that autonomically manages the forwarding protocols and mechanisms of the node in order to optimize the forwarding behaviour of the node so as to meet certain objectives. The Use Case also includes the aspect by which GANA NET_LEVEL_FWD_DE provides logic, algorithms to ensure optimized forwarding of traffic flows in the network and in respect of network operator policies and in order to optimize the network's traffic engineering and forwarding objectives and behaviours. NOTE 1: ETSI TS 103 195-2 [i.2] provides more details of these two DEs, guidance on how to design their associated Control-Loops, and how they complement and interwork with other when both are implemented for the targeted network architecture and its associated management and control architecture. NOTE 2: There already exists in literature some research and implementation and validation work published on such autonomics use case, some of which are based on the GANA framework and IPv6. For example, readers may find work in [i.1], [i.46], [i.45], [i.48] and [i.62] very useful in this regard. 5.6 Autonomic QoS and QoE Management and Control Use Case This is an Autonomics Use Case by which GANA FUNC_LEVEL_QoS_M_DE provides logic, algorithms to ensure QoS for services and improve QoE of services within the GANA node and other nodes through the collaboration of their FUNC_LEVEL_QoS_M_DEs. The Use Case also includes the aspect by which GANA NET_LEVEL_QoS_M_DE provides logic and algorithms to ensure QoS of services and also improve Quality of Experience (QoE) for services. NOTE 1: ETSI TS 103 195-2 [i.2] provides more details of these two DEs, guidance on how to design their associated Control-Loops, and how they complement and interwork with other when both are implemented for the targeted network architecture and its associated management and control architecture. In elaboration of the GANA autonomics by the GANA NET_LEVEL_QoS_M_DE, Autonomic Management Software (the GANA Quality of Service (QoS)-Management DE or a Combined Quality of Service (QoS)-and-Quality of Experience (QoE) Management DE) autonomatically configures resources associated with specific connectivity paths or Network Slices within the network segment the GANA KP is responsible for, such that Traffic Flows (e.g. IP Flows) carried over the paths experience KPIs (e.g. delay, throughput, bandwidth, etc.) that fulfil Service Level Agreements (SLAs) for those flows. The Autonomic Management Software (GANA KP Autonomic Performance-Management DE) also computes various paths within the network segment that should fulfil certain SLAs and is able to adaptively switch traffic flows onto another working path(s) in the event of detected or predicted failures/errors/faults on the primary path(s). Autonomic Management Software (GANA KP Autonomic Performance-Management DE) also continuously monitors and measures network and service performance Key Performance Indicators (KPIs), i.e. any performance degradations, and dynamically allocate resources in its network segment that help to achieve certain KPI targets for traffic flows in particular. NOTE 2: There already exists in literature some research and implementation and validation work published on such autonomics use case, some of which are based on the GANA framework and IPv6. For example, readers may find work in [i.1], [i.54], [i.47], [i.46], [i.48], [i.52] and [i.62] very useful in this regard. ETSI ETSI TR 103 858 V1.1.1 (2026-03) 19 |
7470f1226238696862acc2f2b74c08a3 | 103 858 | 5.7 Autonomic Monitoring Management and Control Use Case | This is an Autonomics Use Case by which GANA FUNC_LEVEL_MON_DE provides logic and algorithms to orchestrate monitoring MEs or to (re)-configure them, and to retrieve information from various potential sources of monitoring data and information in order to intelligently cause dissemination of monitoring data needed by DEs within the node to the local DEs by causing the Monitoring MEs to disseminate the monitoring data required by the local DEs or to register the DEs to receive monitoring data or information of interest to them if available through the Monitoring DE itself. The Monitoring DE also pushes monitoring data to external Data Collectors of the network. The FUNC_LEVEL_MON_DE's logic should include an algorithm to retrieve information (subscribe for information) and process the information indicative about the operations of the GANA node in order to infer and adaptively enforce the monitoring behaviour and monitoring-data flow of the GANA node that is needed by DEs within the node. The Use Case also includes the aspect by which GANA NET_LEVEL_MON_DE provides logic and algorithms to retrieve monitoring data from various sources, to derive context information, to dynamically orchestrate and regulate monitoring mechanisms and tools of the network and the rate (e.g. sampling rate) at which they create monitoring data and disseminate the data to entities that need the monitoring data (e.g. DEs). The granularity and formats in which monitoring data and/or knowledge presentation is created by monitoring mechanisms and tools and disseminated to data collectors and to entities that directly consume the monitoring data or knowledge are all determined by the Monitoring DEs at the Function-Level and Network-Level collaboratively. The Network-Level Monitoring-DE policies the behaviours of Function-Level-Monitoring Management-DEs that dynamically orchestrate and autonomically manage Monitoring Protocols, Mechanisms and Tools of their respective GANA nodes. In orchestrating and managing the mechanisms and tools for disseminating monitoring data, context and knowledge to other DEs in the Knowledge Plane, the Network-Level-Monitoring Management-DE is supposed to orchestrate and dynamically manage and control the kinds of mechanisms and tools for the dissemination of monitoring data, context or knowledge that complement the ONIX and (amc)-MBTS as information/data/knowledge disseminators. The NET_LEVEL_MON_DE's logic should include an algorithm to retrieve information (subscribe for information) and process the information indicative about the operations of the Knowledge Plane DEs in order to infer and adaptively enforce the monitoring behaviour and monitoring-data flow (or knowledge flow) from NEs, Data Collectors and Probes as may be needed by Knowledge Plane DEs during their operations. NOTE 1: ETSI TS 103 195-2 [i.2] provides more details of these two DEs, guidance on how to design their associated Control-Loops, and how they complement and interwork with other when both are implemented for the targeted network architecture and its associated management and control architecture. NOTE 2: There already exists in literature some research and implementation and validation work published on such autonomics use case, some of which are based on the GANA framework and IPv6. For example, readers may find work in [i.1], [i.51], [i.58], [i.46], [i.48] and [i.62] very useful in this regard. |
7470f1226238696862acc2f2b74c08a3 | 103 858 | 5.8 Autonomic Security Management and Control Use Case | This is an Autonomics Use Case by which GANA NODE_LEVEL_SEC_M_DE is used to manage any security issues in the Node. NODE_LEVEL_SEC_M_DE may also be used to secure and authenticate interactions between DEs and MEs within the same domain or to secure interaction with other MEs and DEs within different domain. The Use Case also includes the aspect by which GANA NET_LEVEL_SEC_M_DE is used to manage any security issues in the network. NET_LEVEL_SEC_M_DE may also be used to secure interactions between DEs and MEs within the same domain or to secure interaction with other MEs and DEs within different domain. ETSI ETSI TR 103 858 V1.1.1 (2026-03) 20 |
7470f1226238696862acc2f2b74c08a3 | 103 858 | 5.9 Autonomic Fault Management Use Case | This is an Autonomics Use Case by which GANA NODE_LEVEL_FM_DE is for autonomic fault management within the GANA Node by employing appropriate Fault Detection Mechanisms, Fault Isolation/Localization/Diagnosis Mechanisms, and Fault Removal Mechanisms that enable to repair the node's components and the node as a whole. NODE_LEVEL_FM_DEs of various GANA nodes may collaborate in achieving distributed autonomic fault-management that requires the collaboration of various nodes. The Node-Level-Fault Management-DE (NODE_LEVEL_FM_DE) interworks with the Node-Level-Resilience & Survivability-DE (NODE_LEVEL_R&S_DE) as described in [i.14] and in ETSI GS AFI 002 [i.12]. The Use Case also includes the aspect by which GANA NET_LEVEL_FM_DE is for autonomic fault management that require to be orchestrated at the network level by logically centralized algorithms of the NET_LEVEL_FM_DE-by employing appropriate Fault Detection Mechanisms, Fault Isolation/Localization/Diagnosis Mechanisms, and Fault Removal Mechanisms that enable to repair network services and/or functionality of a network node. The Network-Level-Fault Management-DE (NODE_LEVEL_FM_DE) interworks with the Network-Level-Resilience_&_Survivability-DE (NODE_LEVEL_R&S_DE) as described in [i.14] and in ETSI GS AFI 002 [i.12]. This is an Autonomics Use Case by which Autonomic Management Software (GANA Autonomic Fault-Management DE) automatically detect faults/errors/failures and perform fault-diagnosis and self-repair to sustain a high degree of availability, reliability and acceptable service delivery to end-users. 5.10 Autonomic Resilience & Survivability Management Use Case This is an Autonomics Use Case by which GANA NODE_LEVEL_RS_DE provides logic, algorithms to ensure the resilience and survivability of the node(system) and the network (of some scope) in collaboration with other peer NODE_LEVEL_RS_DEs in other GANA nodes. The Node-Level-Resilience &Survivability-DE (NODE_LEVEL_R&S_DE) interworks with the Node-Level-Fault Management-DE (NODE_LEVEL_FM_DE) as described in [i.14] and in ETSI GS AFI 002 [i.12]. The Use Case also includes the aspect by which GANA NET_LEVEL_R&S_DE provides logic and algorithms to ensure the resilience and survivability of the network systems (network nodes/functions) as described in [i.14] and in ETSI GS AFI 002 [i.12]. |
7470f1226238696862acc2f2b74c08a3 | 103 858 | 5.11 Autonomic Performance Management Use Case | This is an Autonomics Use Case by which Autonomic Management Software (GANA Autonomic Performance-Management DE) monitors and measures network and service performance Key Performance Indicators (KPIs), i.e. any performance degradations, and dynamically allocate resources in the network that help to achieve certain KPI targets. NOTE: There already exists in literature some research and implementation and validation work published on such autonomics use case, some of which are based on the GANA framework and IPv6. For example, readers may find work in [i.48] and [i.1] very useful in this regard. ETSI ETSI TR 103 858 V1.1.1 (2026-03) 21 6 IPv6-Only based E2E 5G Networks: E2E Aspects of IPv6 in 5G and Reference Architecture Scenarios for Consideration; Implications on GANA Autonomics 6.1 Background of SRv6 technology and the motivation in the context of Network Automation This clause aims at showing how to utilize IPv6 capabilities and emerging IPv6 Extensions (e.g. Segment Routing version 6 "SRv6") in the big picture of an "Autonomic-based AI and Programmable 5G Network". Hence, the way it transforms the current complex "5G IP Bearer Network" into a simplified "E2E Programmable Bearer Network" under the paradigm of "Network as a Computer". This clause highlights the Business and Technical benefits SRv6 technology brings in this space. Then, it succinctly presents the SRv6 fundamentals along with the standardization journey and readiness/maturity level and its adoption by Services Providers, Public Sector as well as Products & Solutions Suppliers. Segment Routing version 6 (SRv6) is a protocol defined by the Internet Engineering Task Force (IETF) that aims at simplifying the operations in a packet network. It is a key enabler of next-generation packet networks to effectively support advanced transport services as demanded by 5G, IoT, and Cloud applications. SRv6 is based on two foundational technologies: 1) the Internet Protocol version 6 (IPv6); and 2) the Source Routing paradigm. IPv6 received renewed interest in the past few years [i.15]. National Authorities and Regulators have issued policies to further incentivize the use of IPv6 and prepare the stage for IPv4 sunsetting. Some Service Providers have even moved to IPv6-only networks [i.16], [i.17]. Source Routing is an internet routing technique, originally proposed by Carl A. Sunshine [i.18], in which the packet source, typically the network ingress router, specifies the complete path the packet takes across the network. In doing that, no routing decision (states) needs to be taken at the intermediate nodes, thus simplifying the overall packet processing. SRv6 leverages on two key technical capabilities to provide business benefits: 1) Simplification of Network Management and reduction of OPEX. SRv6 operations require a reduced protocol stack if compared to current IP/MPLS networks. As a result, simplified network operations are achieved, bringing to lower Operational Expenditure (OPEX) for Service Providers. 2) Increase of Quality of Experience (QoE). SRv6 enables both network programmability and network slicing, increasing QoE and allowing resource-based traffic steering. Such a capability fulfils the 5G and Cloud requirements for better control and usage over the Transport Network resources, indispensable for advanced applications as in the case of massive Machine Type Communications (mMTC), Ultra-Reliable Low-Latency Communications (URLLC) and Edge Cloud services. From ETSI side [i.21], SRv6 is characterized by the following 5 key Technical Benefits: simplified network protocols, cloud-network convergence, compatibility with existing networks, enhanced inter-AS connectivity, and agile service provisioning. 6.2 Value of IPv6 in 5G network, and consideration of GANA Multi-Layer Autonomics in the picture In this clause a set of selected architectural scenarios on IPv6 in 5G Networks are presented, and then insights on the impact of introducing GANA Autonomics into the Architectures and the interplay of some key aspects in the architectures with GANA autonomics are provided. ETSI ETSI TR 103 858 V1.1.1 (2026-03) 22 NOTE 1: Insights on how the GANA Knowledge Plane (KP) Platform integrates with other management and control systems (such as SDN controllers and NFV MANO, OSS/BSS and Service Orchestrators, etc.) and the network are provided in clause 4. 5G SA Core architecture enables to select for each 5G connection the application located in the best datacentre type (edge, regional, core) and the best path to deliver appropriate QoE for each Service. At the same time, it wants to have the lower impact possible in resource utilization and related power consumption to fulfil the service need, avoiding network over-dimensioning and relative costs. Figure 1a: 5G core reference architecture (ETSI TS 123 501 [i.22]) with functional distribution in a 3-levels DCs structure (Courtesy of ETSI GR IPE 005 [i.65]) In this scenario, the transport network plays a relevant role. IPv6 and SRv6, together with multiple other state of the art technologies, enable to fulfil those functionalities at best. Old technologies like IPv4, present a specific limitation that does not allow to exploit 5G SA core functionalities. Private IPv4 has to be reused multiple times within the operator network, and vertical access islands need to be created in order to avoid address overlap. This limits the possibility of freely using any UPF within the network. The location of the application is not freely selectable. ETSI ETSI TR 103 858 V1.1.1 (2026-03) 23 Figure 2: GANA instantiation onto specific network segments, including GANA instantiation onto the 5G core reference architecture (ETSI TS 123 501 [i.22]) with functional distribution in a 3-levels DCs structure NOTE 2: Considerations for NWDAF/MDAF (NWDAS/MDAS) should be taken into consideration regarding the integration of these functions/services with the GANA KP Platform as described earlier in clause 4.3 of the present document (particularly in Figure 1 on "integration of the GANA Knowledge Plane (KP) with various management and control systems through which the Knowledge Plane can selectively program the network; and KP integration with Event Sources, Data Sources and Info/Knowledge Sources"). |
7470f1226238696862acc2f2b74c08a3 | 103 858 | 6.3 Slicing in packet networks | |
7470f1226238696862acc2f2b74c08a3 | 103 858 | 6.3.1 Network Slicing high level architecture | Network slicing is one of the biggest differentiators of 5G compared to previous generations of mobile services. Network slicing brings increased network resource utilization efficiency and deployment flexibility. It also provides a higher quality of experience in servicing the differentiated requirements of customers and applications. From the network's perspective, the concept of slicing is discussed in [i.25]. There, "network slicing" is analysed within the context of IETF. [i.25] introduces the term "IETF Network Slice", which specifies a slice is implemented over the technologies identified by the IETF (e.g. MPLS, SR, SRv6, etc.), its characteristics and system components. 3GPP defined network slicing as a critical 5G Core (5GC) feature in [i.22]. A network slice is viewed as a logical end- to-end network that can be dynamically created, modified or deleted. A User Equipment (UE) may access to multiple slices over the same Access Network (AN). This latter is typically the 3GPP Radio Access Network (RAN), but it can also be a non-3GPP Access Network where the terminal may use any non-3GPP access to reach the 5GC, for example, via a secured IPSec/Internet Key Exchange (IKE) tunnel over a Wi-Fi® network. ETSI ETSI TR 103 858 V1.1.1 (2026-03) 24 E2E slice spanning various network segments (e.g. Access, Transport, Core) leverage on the above definitions from IETF and 3GPP. Each slice may serve a particular service type, set of applications or group of customers, each with an agreed upon Service Level Agreement (SLA). The Access and Mobility Management Function (AMF) instance serving the UE is common (or logically belongs) to all the Network Slice instances that are serving the UE. Other network functions, such as the Session Management Function (SMF) or the User Plan Function (UPF), may be specific to each Network Slice. This is represented in Figure 3, which shows two different slices (both Red and Green). Figure 3: Network slicing high-level architecture (SRv6 in the backhaul network) (Courtesy of ETSI GR IPE 005 [i.65]) The network slice instance selection is triggered as part of the registration procedure by the first AMF that receives the registration request from the UE. The AMF retrieves the slices allowed by the user subscription and interacts with the Network Slice Selection Function (NSSF) to select the appropriate Network Slice instance. In the IPv6-based 5G transport network, SRv6 programmability is essential to support 5G network slicing. The IPv6 data plane still uses both IGP (Interior Gateway Protocol) and BGP (Border Gateway Protocol) protocols to carry the routing and reachability information of the network nodes. The only extension requested is the support of multi- topology in [i.23] and [i.24]. In addition, SRv6 network programming [i.19] enables network slicing support through fine-grained packet handling and steering. |
7470f1226238696862acc2f2b74c08a3 | 103 858 | 6.3.2 SRv6 based network slicing | SRv6 is the more suitable protocol to underpin Network Slicing in 5G network. Possibility to define connection flow spanning the whole network provide benefits in service creation and monitoring. Traffic Engineering policies can be prescribed to network slice instances and implemented in different sections of the network. SRv6, spanning the whole network, simplify the network in term of number of protocols used and interworking functions, as well as straight-forwarding the service lifecycle. It enables easy creation, modification and monitoring of each connection flow. It underpins properly the management system automation of the whole service lifecycle. Different SRv6 SIDs are allocated per node, each associated with a slice. Every Segment Identifier (SID) is also related to specific network resources. This way, a node receives as many SIDs as the slices it is part of. The physical network is decomposed in a virtual link with specific QoS. Each of those virtual links can be assigned to one or multiple slices. Flexible Ethernet (Flex-E) protocol could be used for this scope, to dedicate proper bandwidth and priority to each slide according to the needed SLA of the associated 5G Slice. (NSSAI) (NSSAI) UE RAN AMF NSSF NRF UPF SMF UPF SMF DN1 DN2 PCF PCF NRF NRF Backhaul Network Common Network Functions Slice 2 (Green) Slice 1 (Red) ETSI ETSI TR 103 858 V1.1.1 (2026-03) 25 For each of those Flex-E links, a specific SID is associated, with the possibility for routing protocol to select the proper Flex-E link according to the needed QoS. Each SID has a locator dedicated to a specific slice, as shown in Figure 4. Figure 4: Network slicing based on FlexE, FlexALGO and SRv6 locators The identification of a network slice is guaranteed by a specific locator assigned to a node. The example above shows that Communication Systems Group (CSG)-1 belongs to the "Red" slice. A loopback address in the form of A1:1::1 is then associated with CSG1. A1:1 is the locator of the node (the first part, A1), while the slice is identified by the following 1 (the third and fourth bytes of the address in the example). The transport network will result to be composed of several Flex-E links with different QoS. The node pre-Aggregation Gateway(Pre-AGG)-1 support forwarding for two slices. This way is associated with two loopback addresses: a first one A2:1::1 is for the "Red" slice and a second one A2:2::1 for the "Blue" slice. Once again, A2 is the locator of Pre-AGG-1, while the following number is the slice identifier. SR paths are normally configured based on the metrics provided by IGP protocols. In such a case, SR Best Effort (SR-BE) is considered, as paths are built upon the Shortest Path First (SPF) mechanisms. The path to a destination is thus calculated by minimizing the topological cost, normally associated with the link cost. To address the lack of flexibility imposed by SPF, Flexible Algorithm (Flex-Algo) technology is introduced. A Flex-Algo allows an IGP to calculate constraint-based network paths, implementing Traffic Engineering (TE) capabilities in an easier and more flexible manner. Flex-Algo technology IETF RFC 9350 [i.26] provides some technical advantages, such as: • NEs involved in the same Flex-Algo natively form an independent logical topology. Also, constraints of the IGP path algorithm can be defined to further exclude some links in the logical topology. • The types of metrics used in the IGP path algorithm can be defined. In addition to the link cost value, SPF algorithm can calculate the shortest path to the destination based on the link delay and TE metric values. This way Flex-Algo can meet the requirements of different services, including high-bandwidth and low-delay services. Flex-Algo can be natively used on SR networks and is compatible with "Equal-Cost Multi-Path" (ECMP) load balancing and Topology Independent-Loop Free Alternate" backup paths in these networks. [i.26] specifies a set of extensions to Intermediate System-to-Intermediate System (IS-IS), "Open Shortest Path First" version 2 OSPFv2, and OSPF version3 that enable a router to advertise through Type-Length-Values TLVs the key characteristics of a Flex-Algo. Often, flexible algorithms are seen as the enabler of advanced applications, such as network slicing, in carrier's networks. While this is generally true, flexible algorithms may find utilization also in enterprises and utilities. The differentiated handling of applications, based on their diversified SLAs, may require having multiple logical topologies also in the context of a factory, campus or purpose-built network. Grid networks, as an example, may take benefit of diversified topologies each carrying an application which is characterized by low latency or strict availability. SRv6 SIDs inherit the slice identification from Locator. The resulting virtual topology is shown on the right. The two slices have dedicated topology and associated behaviour as represented in Figure 4. One of the slices may be tuned for policies that enable low-latency transport or higher capacity or other metrics/parameters for an optimized transport that best serves a service's requirements. ETSI ETSI TR 103 858 V1.1.1 (2026-03) 26 To achieve this step, the control plane or the network controller (or a combination of the two) has to distribute the information about the network resources associated with a slice. This information distribution is based on the multi-topology concept, already supported by the IGP protocols. This is capable of propagating routing information associated to multiple virtual topologies enabled over the same physical network [i.23] and [i.24]. In order for SRv6-TE to take into consideration link characteristics such as latency and other TE constraints, a flexible routing algorithm (or flex-algo) has to be enabled on the control plane. Flex-Algo (0) to Flex-Algo (127) are reserved by the Internet Assigned Numbers Authority (IANA) as standard algorithms. Flex-Algos from 128 onwards are instead used for customizable path computation (e.g. with the lowest latency). The specific computation may be propagated through either IGP control protocols or policies issued by an SDN controller. This latter may represent a better option as it has a centralized knowledge of the whole network. Assuming an SDN controller is employed, this will build a TE database of the network and, based on the service requirements, assign SIDs, in the form of locator:function, to all the nodes involved. The structuring of a SID into the locator:function form is the second, indispensable pre-requirement to enable network programming and support TE mechanisms. The SRv6 SID function is the identifier of a "behaviour" defined locally to the locator (node). More formally, it takes the name of SRv6 Endpoint behaviour. |
7470f1226238696862acc2f2b74c08a3 | 103 858 | 6.3.3 SR-based network programming | Network programming combines Segment Routing functions, both topological and service, to achieve a networking objective that goes beyond mere packet routing. The concept of network programming comes from computer programming. In computer programming, human beings can translate their intentions into a series of instructions that computers can understand, computers execute the instructions to realize the human intent. Correspondingly, network programming translates intent into a series of forwarding instructions that network devices can understand, the network executes the instructions to realize the intent. SRv6 network programming [i.20] defines a base set of SRv6 endpoint behaviours. A network program is built from Segment IDs (SIDs), that are 128 bit opaque identifiers for a local endpoint behaviour. In other words, a SID represents a local action or policy at a node, such as forwarding a packet via an adjacency, or decapsulating and forwarding an inner packet via a Virtual Routing and Forwarding (VRF) table toward its destination. SRv6 SIDs are treated as IPv6 addresses by the network when they are in the IPv6 header destination address field. The network simply forwards packets destined to SIDs toward the node implementing the SID. The 128bit SRv6 SID consists of three parts: 3) Locator, encoded in the most significant bits of the SID: a) The uppermost bits of a locator is called the Block, this is the block of the IPv6 address space SIDs are assigned from. b) The remaining bits of the locator identify the Node the SID is located on. 4) Function, encoded in the next most significant bits of the SID, identifies the local behaviour, and any local semantics for that behaviour, to be executed at the node. 5) Optional arguments, encoded in the next most significant bits of the SID, identify arguments to the function. The semantics and format of argument bits are defined by the endpoint behaviour specification. SR policies [i.27] define an instantiated network program as a segment list. SR policies contain multiple candidate paths between an SR source and endpoint. Traffic is steered into an SR policy to apply a network program to it, such as traffic engineering i.e. to forward traffic via a low latency path, a disjoint path, a service function chain, or any network program represented as a list of SIDs. Through policies it is possible to define differentiated handling for traffic flows, i.e. Traffic Engineering (TE). As an example, one policy between two endpoints may specify a low-latency path (e.g. to serve a time-bound mission critical application), another policy between the same two endpoints may specify a high-capacity path (e.g. to carry best-effort traffic). SR Traffic Engineering (SR-TE) applies to both carrier and enterprise networks. The enablement of SR-TE in the backbones provide a sort of unification of the protocols used. SR-TE based on IPv6 may become the common underlay to enable multi-domain connectivity to transport all services, no matter whether they are legacy or new innovative applications. ETSI ETSI TR 103 858 V1.1.1 (2026-03) 27 SR-TE can be combined with SDN, for example, through SR Path Computation Engine (SR-PCE) [i.28]. SR-PCE provides scalable multi-domain, engineered path computation capabilities, and enables communication from a centralized SDN controller to the headend node at the ingress of a SR-TE domain and in charge of steering a traffic flows across it. This may be applicable in those cases where automatic tunnel configuration is requested, to simplify the operational processes and reduce state in networks. It is worth mentioning that the SRv6 network programming based on SID, Locator, Function and SR-TE Policies is complementing the GANA-based Programmable Network [i.29]. |
7470f1226238696862acc2f2b74c08a3 | 103 858 | 6.3.4 Application-aware Networking | There are proposals in the IETF for APplication-Aware Networking (APN), for which a working group is being considered. One of the key objectives of APN is for the network to provide fine-grain SLA guarantees instead of coarse-grain traffic operations. Among various applications being carried and running in the network, some applications have much more demanding performance requirements such as low network latency and high bandwidth. In order to achieve better Quality of Experience (QoE), the network needs to be able to provide fine granularity and even application-level SLA guarantee. MPLS dataplane is rarely used at the packet origin (i.e. Branch Office) and therefore it is not possible to assume the MPLS encapsulation is available end-to-end in the traffic flow journey. So IPv6/SRv6 dataplane provides a better option for APN due to its flexibility, address space and further developments of SRv6 [i.19] and [i.20]. When APN applies to the IPv6/SRv6 dataplane, it is referred as "APplication-aware IPv6 Networking (APN6)". APN6 conveys information into the network infrastructure about the characteristics of the application associated with a traffic flow (including application identification and network performance requirements), using IPv6/SRv6 encapsulation allowing the network to quickly adapt and perform the necessary network resource adjustments to maintain SLA performance guarantees, and hence better serve application fine-grained service requirements. APN6 may fit well with the Software-Defined Wide Area Network (SDWAN) architecture. |
7470f1226238696862acc2f2b74c08a3 | 103 858 | 6.3.5 SRv6 and SDWAN | With the adoption of the public cloud reliable and efficient data interconnection is critical. The solution to build a high performance Wide Area network (WAN) is given by Segment Routing over IPv6 (SRv6 and SDWAN technologies SRv6 brings several key benefits. First, it connects enterprise sites and clouds by programming end-to-end paths at ingress nodes via source routing. It accomplishes this by leveraging routing protocols (OSPF or IS-IS) to distribute segment identifiers and utilizes them in the IPv6 destination address of the IPv6 header, as well as in the Segment Routing Header (SRH) extension header (see clause 6.3.2.). SDWAN will make network entities plug-and-play, allowing branches to be connected to the cloud in one hop and achieve network connectivity immediately. SDWAN can employ intelligent traffic steering and make full use of multiple link resources such as 5G and private lines, by choosing the optimal link to transmit traffic of key applications, and forward different types of traffic along different paths. The combination of SDWAN with an SRv6 underlay can provide significantly more path choices for the SDWAN to steer traffic on. 6.4 IPv6-only in 5G SA user plane based on 464XLAT/NAT64+DNS64 IPv6-only in 5G SA user plane based on limited IPv4 connectivity across an IPv6-only network (464XLAT) combined with Network Address Translation IPv6 addresses into IPv4 addresses (NAT64) and a Domain Name System (DNS) service that returns AAAA records (AAAA records to specify the IPv6 address of the server that contains Uniform Resource Locator site) with these synthetic IPv6 addresses for IPv4-only destinations(DNS64). This clause discusses the possible IPv6-only transition solutions, and the process of selecting one of them to fit the need. ETSI ETSI TR 103 858 V1.1.1 (2026-03) 28 [i.15] reports the most common transition solutions for IPv6-only service delivery, 464XLAT, Dual Stack Lite is an architecture that allows IPv4 services to be provided in an IPv6 network (DS-lite), Lightweight IPv4 over IPv6 (lw4o6) An Extension to the Dual-Stack Lite Architecture (IETF RFC 7596 [i.72]), that MAP-T (IETF RFC 7599 [i.73]) translates the IPv4 header to the IPv6 header (and vice versa), MAP-E (IETF RFC 7597 [i.74]) encapsulates the entire IPv4 packet into the IPv6 packet. For Mobile BroadBand (MBB), the IPv6 hosts (e.g. the Apps on the UE) behind the IPv6-only Customer-Premises Equipment (CPE) (i.e. the User Equipment (UE) itself) can natively access IPv6 websites or services. However, in order to access IPv4 websites, NAT64 and DNS64 are needed. NAT64 [i.31] is needed to accomplish the translation. DNS64 [i.32] is likely needed too, assuming DNS queries are required, see Figure 16. Note that Figure 5 shows how an IPv6-only host accesses an IPv4 website. Figure 5: NAT64+DNS64: how they work (source: Wiki) But "NAT64+DNS64 is not sufficient for all scenarios. For example, when an IPv6-only UE is serving as a hotspot, some tethering devices may only support IPv4. To support such IPv4 hosts behind an IPv6-only CPE, 464XLAT [i.33] is a suitable choice, because 464XLAT consists of a "Client-side NAT46" (CLAT) at the CPE and a "Provider side NAT64" (PLAT), see Figure 6. PLAT is identical to the one described in the first case, while CLAT at the CPE can translate the IPv4 traffic from the IPv4 hosts into IPv6 traffic. So with 464XLAT, this second scenario effectively becomes the first scenario. On the provider side, NAT64 is the only NAT, and both IPv4 and IPv6 hosts behind the IPv6-only CPE will work, for any kind of website." Figure 6: Overview of the 464XLAT (IPv4 as a service on top of IPv6 network) "Note that most of the mobile UE Operating System Embedded (Ose) support the client part of 464XLAT (provider part of 464XLAT is not relevant to mobile OSes). Furthermore, according to [i.30], mobile OSes generally do not support other IPv6-only transition solutions. Consequently, 464XLAT can be considered to be effectively the only IPv6-only solution for MBB. For FBB and enterprises, if the CPEs support 464XLAT, in particular CLAT, then it is the recommended IPv6-only solution. In this way, MBB, FBB and enterprises can apply the same solution, and NAT64 will be the only NAT. This can simplify network operations and management and reduce OPEX. ETSI ETSI TR 103 858 V1.1.1 (2026-03) 29 If the operators' CPEs do not support 464XLAT, then the DS-Lite IPv6 transition solution is a viable alternative. It is important to mention that many existing fixed IPv6-only deployments use DS-Lite, possibly due to the fact that DS-Lite was the first IPv6-only transition solution that was published, indeed DS-Lite [i.34] was published in Aug. 2011, while 464XLAT [i.33] was published in April 2013. Figure 18 provides an overview of the DS-Lite architecture. The IPv6 traffic will be transported natively; IPv4 traffic will be tunnelled from Basic Bridging Broadband (B4) to Address Family Transition Router (AFTR), where traffic will be decapsulated and NATted. The solution is comparable to 464XLAT in terms of technical merit, but it is different from the IPv6-only solution used for MBB. This could mean that operators will need to deploy two different NATs, NAT64 for MBB and NAT44 for FBB." [i.67] Figure 7: Overview of DS-Lite architecture (IPv4 tunnel in IPv6 network) Based on the above discussion Dual-Stack is recommended as the IPv6 transition solution for IPv6 introduction in the early-stage, and 464XLAT / DS-Lite for the IPv6-only service delivery. Note that MAP-T translates the IPv4 header to the IPv6 header (and vice versa), MAP-E encapsulates the entire IPv4 packet into the IPv6 packet . Theyhave clear technical merit for the Fixed BroadBand (FBB) scenario [i.35] defines the Test Purpose, the Test Descriptions and the Abstract Test Suite (ATS) for IPv6-only services over 5G. |
7470f1226238696862acc2f2b74c08a3 | 103 858 | 6.5 Network Automation and SDN | In the new world of networking, Network Functions Virtualisation (NFV) and Software-Defined Networking (SDN) are new paradigms in the move towards open software and network hardware. While NFV aims to virtualize network functions and deploy them into general-purpose hardware, SDN makes networks programmable by separating the control and data planes. NFV and SDN are complementary technologies capable of providing one network solution. NOTE: Insights on how the GANA Knowledge Plane (KP) Platform integrates with other management and control systems (such as SDN controllers and NFV MANO, OSS/BSS and Service Orchestrators, etc.) and the network are provided in clause 4. In this context, every network can benefit from the centralized model of NFV/SDN, rather than staying with networks that operate on the decentralized model of the Internet. In particular, the use of NFV/SDN can help to achieve levels of performance, resource optimization, and user responsiveness that are unthinkable in decentralized networks. There are some considerations about the moving of a network to use SDN. SDN can lower operating costs (OPEX) because most of the operating costs in a network are in network management. SDN provides new ways to centralize, automate and therefore simplify network management. Many tasks are made easier, such as changing switch/router configurations, adding new nodes to the network, detecting network issues, resolving these issues and maintaining security. The SDN automation also facilitates insight into the network and this is key for reducing the cost of network management. SDN does not impact substantially on capital expendure costs (CAPEX), indeed networking equipment are reliable, secure, high performing, power-efficient, and more, so the cost of building the equipment is not changing. Moving to SDN allows faster introduction of new capabilities into the network. The intelligence is out of the switches/routers and into the controller/orchestrator. This means that the network functionality can be enabled through software and installed faster in the network. Hence, SDN relies on stable communication between network nodes and the controller. Ensuring the reliability of this critical communication path is very important. SDN can improve network security, indeed security depends on blocking malicious users and malicious traffic. The SDN controller helps to ensure rapid and automated detection and to block malicious traffic within the network. ETSI ETSI TR 103 858 V1.1.1 (2026-03) 30 In addition, SDN can provide a better experience for the end users of the network. As new devices and services become available, users want to adopt them as soon as possible. So in the network it is required a high level of flexibility and the network infrastructure should be dynamic and responsive. SDN can automatically adapt to dynamic changes and enhance the user experience. As described in [i.36], SDN also helps with the IPv6 transition; in particular the SDN Controller can guide IPv4 / IPv6 traffic to the appropriate network function (or virtual network function) automatically, the NFV allows the Internet Service Provider (ISP) to deploy virtual IPv4 / IPv6 network function in the same infrastructure. Thanks to SRv6 SDN controller interactions, ISP can grant the SLA e2e even in the customer premises network, cloud network and service lan consistently. 6.6 IPv6/SRv6 Operations Administration and Maintenance (OAM) tools and Automation (mapping with GANA) Thanks to the extensibility of the IPv6 protocol, new methodologies for telemetry and performance measurements can be used. In-situ Flow Information Telemetry (IFIT) denotes a family of flow-oriented on-path telemetry techniques which can provide high-precision flow insight and real-time network issue notification (e.g. jitter, latency, packet loss). Alternate Marking, defined in [i.37] and [i.38], enables a flexible approach to network management that can be combined with SDWAN. As said, SDWAN allows connecting remote branch offices to data centres and building higher-performance WANs. This helps ensure that application performance meets Service Level Agreements (SLAs). The Alternate Marking methodology [i.37] and in particular its application to multipoint flows can also help the path selection for the WAN connection based on per-cluster and per-flow performance measurement and analytics as described in [i.38]. These new emerging techniques for telemetry and performance measurements are bringing out a new paradigm to allow Closed Loop Automation. It means that the relation between the Controller and the network is now bidirectional and the telemetry information can help the controller to decide accordingly. Since SDN Automation is now evolving and Yet Another Next Generation (YANG); a data modeling language; is now everywhere as a configuration language for networking, this approach is also known as Model Driven. Figure 8: Closed loop automation for IPv6/SRv6 Network ETSI ETSI TR 103 858 V1.1.1 (2026-03) 31 NOTE: While Telemetry should be fed to the GANA KP Platform, it is important to note that the GANA framework also provides for principles by GANA DEs introduced to run within Network Elements/Functions (NEs/NFs) as GANA Nodes help limit the types and volume of telemetry data exported by the NEs/NFs to the KP Platform's DEs or Data Lake as the lower level DEs can perform certain delegated decisions based on observations (views) accessible by the DEs at that low level while the lower level DEs then export only some reports to the GANA KP Platform level's Network Level DEs. NEs/NFs within embedded DEs should still be configured to export certain types and volume of monitoring data to an external Data Lake and/or to the GANA KP Platform responsible for the NE/NF. These aspects on need and benefits to limiting the types and volume of monitoring data that may be exported by NEs/NFs are covered in ETSI TS 103 195-2 [i.2] dissertation on autonomics in multi-layer transport networks]. Applications, IP Flows, or Services that utilize the network or network slices should be made to provide (directly or indirectly) end-to-end requirements (e.g. acceptable end to end latency, throughput, jitter, security requirements, etc. as part of SLA) to GANA KP Platforms of the End-to-End so that the KPs act to assure the service offered by the network to fulfil the requires, including collaboratively working together to achieve E2E service assurance and E2E security assurance as required by the SLAs. The Network orchestrator will need to manage the network at multiple layers: • Flex-E configuration needs to be maintained and eventually reconfigured according to foreseen traffic volumes for the different categories of QoS. • Assignment of Flex-E link and nodes to each Hard Slice (as both primary and backup link to be used only in case of failure) has to be dynamically managed. • SRv6 connections have to be established in real-time, determining the proper Hard Slice to be used and the SR path to reach the destination according to the information received by the 5G SA core network. • Service Function Chain can be realized, including in the SR path application information accordingly. • In the event of a fault, activation of backup and quick convergence of the overall transport network needs to be granted. The network design discussed so far moved from the assumption of running a traditional, distributed control plane where each router contributes to the exchange of reachability information through a mix of IGP protocols and BGP. The approach currently adopted by many operators worldwide is to enable network automation through the SDN capability introduced in clause 5.6. In this context, an SDN system becomes the network controller, centralizing the control of the network and becoming the unified point from where policies and configurations are delivered to the network nodes. A way to represent the role in SDN in the centralization of the network control processes is shown in Figure 9. Figure 9: SDN role in an IPv6/SRv6 network ETSI ETSI TR 103 858 V1.1.1 (2026-03) 32 The SDN controller acts as the centralized repository of the configurations of all nodes, retrieved by several mechanisms or protocols, such as Netconf [i.39], Command Line Interface (CLI), Simple Network Management Protocol (SNMP), and others. The SDN controller joins the network control plane, collecting the routing information distributed by the routers in the network. This information includes the IGP and BGP reachability and allows the SDN controller to construct the network topology. In addition to the routing information, the SDN controller also collects the status of the network components (e.g. a router's behaviour or the status of an interface) and the degree of utilization of the network resources. This may be achieved using different technologies (e.g. telemetry protocols, exchange of management data, configuration scripts). A way often found in live networks is BGP Link-State (BGP-LS) [i.40] and [i.41]. BGP-LS has been designed to derive from IGP protocols both the current state of the network connections and the associated TE information and share them with external components. Here an SDN controller finds its perfect fit: as highlighted in Figure 9, the SDN controller receives the BGP-LS updates from the Route Reflectors (RR), which in turn receive them from the other network nodes. As shown, Pre-AGG, AGG, and Provider Edge (PE) devices collect IGP topology, bandwidth, link delay and report such information to RRs by BGP-LS. RRs report it to the SDN controller. Once SDN knows the full network topology, including awareness of the network resources, it can take control over the entire network, implementing functions such as: • Assigning the addresses to each node • Delivering the SRv6 SIDs and locators • Computing the SR policies identified by <Head-end, colour, End-point> • Assigning the relevant resources to a network slice Several mechanisms are also available for an SDN Controller to push the path information down to the network nodes. A way to propagate BGP SRv6 policies (sometimes abbreviated with BGP SR, as shown in Figure 10 is through [i.42]. An SDN controller uses BGP SRv6 to advertise an SR forwarding policy towards a headend node. The SR forwarding policy may include one or more candidate paths, each consisting of more segment lists. The SRv6 forwarding policy is used to describe the path of the IP packets from Source to Destination nodes across the network. ETSI ETSI TR 103 858 V1.1.1 (2026-03) 33 NOTE: Multi-Layer aspect in transport networks usually implies IP and Optical Level. Figure 10: GANA Knowledge Plane (KP) Platform integration with SDN Controllers of Multi-Layer Transport Domains 6.7 Other ETSI IPE Reference Architecture Scenarios for consideration In this clause a set of selected architectural scenarios on IPv6 in 5G Networks are presented, with the aim to add insights on the impact of introducing GANA Autonomics into the Architectures and the interplay of some key aspects in the architectures with GANA autonomics. NOTE 1: Insights on how the GANA Knowledge Plane (KP) Platform integrates with other management and control systems (such as SDN controllers and NFV MANO, OSS/BSS and Service Orchestrators, etc.) and the network are provided in clause 4. Figure 11 presents a 5G security architecture scenario presented in ETSI GR IPE 005 [i.65]. The impact of introducing GANA Autonomics into this architecture scenario is as follows: • The Access part would have a GANA KP associated with it instantiated and with possibility to have GANA levels 2 and 3 DEs introduced into some (possibly all) NEs/NFs of the Access network; • The Transport network part would have a GANA KP associated with it instantiated and with possibility to have GANA levels 2 and 3 DEs introduced into some (possibly all) NEs/NFs of the transport network; • The Security Gateway (SEG) would have GANA Level-3 Security Management-DE instantiated into it to make it autonomic (control-loop based intelligent) in the way it operates; • The Firewall (FW) would have GANA Level-3 Security Management-DE instantiated into it to make it autonomic (control-loop based intelligent) in the way it operates; the core network would have a GANA KP associated with it instantiated and with possibility to have GANA levels 2 and 3 DEs introduced into some NEs/NFs of the core network. ETSI ETSI TR 103 858 V1.1.1 (2026-03) 34 Figure 11: 5G security architecture (Courtesy of ETSI GR IPE 005 [i.65]) Figure 12 presents Typical architecture of a mobile transport network architecture described in ETSI GR IPE 005 [i.65]. The impact of introducing GANA Autonomics into this architecture scenario is as follows: • The transport network would have a GANA KP associated with it instantiated and with possibility to have GANA levels 2 and 3 DEs introduced into some (possibly all) NEs/NFs of the transport network; • The Radio Access network part would have a GANA KP associated with it instantiated and with possibility to have GANA levels 2 and 3 DEs introduced into some (possibly all) NEs/NFs of the Radio Access network. Figure 12: Typical architecture of a mobile transport network architecture (Courtesy of ETSI GR IPE 005 [i.65]) Figure 13 presents High-level architecture of a packet-based (layer-3) mobile transport network described in ETSI GR IPE 005 [i.65]. The impact of introducing GANA Autonomics into this architecture scenario is as follows: • The transport network would have a GANA KP associated with it instantiated and with possibility to have GANA levels 2 and 3 DEs introduced into some (possibly all) NEs/NFs of the transport network; • Instantiation of GANA onto a Telco-Cloud environment follows approach described in ETSI TR 103 473 [i.4]; • The Radio Access network part would have a GANA KP associated with it instantiated and with possibility to have GANA levels 2 and 3 DEs introduced into some (possibly all) NEs/NFs of the Radio Access network. ETSI ETSI TR 103 858 V1.1.1 (2026-03) 35 Figure 13: High-level architecture of a packet-based (layer-3) mobile transport network (Courtesy of ETSI GR IPE 005 [i.65]) Figure 14 presents Multiple Autonomous System Numbers (ASN) in a mobile transport network scenario described in ETSI GR IPE 005 [i.65]. The impact of introducing GANA Autonomics into this architecture scenario is as follows: • The transport network would have a GANA KP associated with it instantiated and with possibility to have GANA levels 2 and 3 DEs introduced into some (possibly all) NEs/NFs of the transport network; • Instantiation of GANA onto a Telco-Cloud environment follows approach described in ETSI TR 103 473 [i.4]; • The Radio Access network part would have a GANA KP associated with it instantiated and with possibility to have GANA levels 2 and 3 DEs introduced into some (possibly all) NEs/NFs of the Radio Access network. Figure 14: Multiple ASNs in a mobile transport network (Courtesy of ETSI GR IPE 005 [i.65]) Figure 15 presents a Routing architecture scenario described in ETSI GR IPE 005 [i.65]. The impact of introducing GANA Autonomics into this architecture scenario is as follows: • The transport network would have a GANA KP associated with it instantiated and with possibility to have GANA levels 2 and 3 DEs introduced into some (possibly all) NEs/NFs of the transport network; • Instantiation of GANA onto a Data Centre (DC) physical network infrastructure follows the approach described in ETSI TR 103 404 [i.5] and if the DC is a virtualized one then the instantiation of GANA onto such virtualized DC network follows approach described in ETSI TR 103 473 [i.4]; • The Radio Access network part would have a GANA KP associated with it instantiated and with possibility to have GANA levels 2 and 3 DEs introduced into some (possibly all) NEs/NFs of the Radio Access network. Internet Telco Cloud / Core Data Center Aggregation Access gNB gNB CSG CSG Pre- AGG Pre- AGG Core GW GW gNB AGG AGG PE PE AS 1 ETSI ETSI TR 103 858 V1.1.1 (2026-03) 36 Figure 15: Routing architecture (Courtesy of ETSI GR IPE 005 [i.65]) Figure 16 presents an End-to-end view, including RAN and Core DC described in ETSI GR IPE 005 [i.65]. The impact of introducing GANA Autonomics into this architecture scenario is as follows: • The transport network would have a GANA KP associated with it instantiated and with possibility to have GANA levels 2 and 3 DEs introduced into some (possibly all) NEs/NFs of the transport network; • Instantiation of GANA onto a Data Centre (DC) physical network infrastructure follows the approach described in ETSI TR 103 404 [i.5] and if the DC is a virtualized one then the instantiation of GANA onto such virtualized DC network follows approach described in ETSI TR 103 473 [i.4]; • The Radio Access network part would have a GANA KP associated with it instantiated and with possibility to have GANA levels 2 and 3 DEs introduced into some (possibly all) NEs/NFs of the Radio Access network. Figure 16: End-to-end view, including RAN and Core DC (Courtesy of ETSI GR IPE 005 [i.65]) ETSI ETSI TR 103 858 V1.1.1 (2026-03) 37 Figure 17 presents End-to-end transport of 5G services described in ETSI GR IPE 005 [i.65]. The impact of introducing GANA Autonomics into this architecture scenario is as follows: • The transport network would have a GANA KP associated with it instantiated and with possibility to have GANA levels 2 and 3 DEs introduced into some (possibly all) NEs/NFs of the transport network; • Instantiation of GANA onto a Data Centre (DC) physical network infrastructure follows the approach described in ETSI TR 103 404 [i.5] and if the DC is a virtualized one then the instantiation of GANA onto such virtualized DC network follows approach described in ETSI TR 103 473 [i.4]; • The Radio Access network part would have a GANA KP associated with it instantiated and with possibility to have GANA levels 2 and 3 DEs introduced into some (possibly all) NEs/NFs of the Radio Access network. Figure 17: End-to-end transport of 5G services (Courtesy of ETSI GR IPE 005 [i.65]) Figure 18 presents VRF-based Service Infrastructure described ETSI GR IPE 005 [i.65]. The impact of introducing GANA Autonomics into this architecture scenario is as follows: • The transport network would have a GANA KP associated with it instantiated and with possibility to have GANA levels 2 and 3 DEs introduced into some (possibly all) NEs/NFs of the transport network; • Instantiation of GANA onto a Data Centre (DC) physical network infrastructure follows the approach described in ETSI TR 103 404 [i.5] and if the DC is a virtualized one then the instantiation of GANA onto such virtualized DC network follows approach described in ETSI TR 103 473 [i.4]; • The Radio Access network part would have a GANA KP associated with it instantiated and with possibility to have GANA levels 2 and 3 DEs introduced into some (possibly all) NEs/NFs of the Radio Access network. Access Aggregation Core gNB gNB CSG gNB VLAN L3VPN on SRv6-BE Core Data Center BS BS L VM VM S CSG Pre- AGG Pre- AGG AGG AGG PE PE L S eBGP (e.g. option A, C) VLAN RR RR RR RR Server Farm L3VPN on VxLAN ETSI ETSI TR 103 858 V1.1.1 (2026-03) 38 Figure 18: VRF-based Service Infrastructure (Courtesy of ETSI GR IPE 005 [i.65]) Figure 19 presents Network OAM protocols considered in ETSI GR IPE 005 [i.65]. The impact of introducing GANA Autonomics into this architecture scenario is as follows: • There are GANA DEs that are responsible for autonomically managing and orchestrating OAM protocols (in particular the Monitoring-DE can be implemented to manage and orchestrate protocols such as Bidirectional Forwarding Detection (BFD), Two-Way Active Measurement Protocol (TWAMP), and Internet Control Message Protocol (ICMP) based monitoring tools/mechanisms); • The transport network would have a GANA KP associated with it instantiated and with possibility to have GANA levels 2 and 3 DEs introduced into some (possibly all) NEs/NFs of the transport network; • Instantiation of GANA onto a Data Centre (DC) physical network infrastructure follows the approach described in ETSI TR 103 404 [i.5] and if the DC is a virtualized one then the instantiation of GANA onto such virtualized DC network follows approach described in ETSI TR 103 473 [i.4]; • The Radio Access network part would have a GANA KP associated with it instantiated and with possibility to have GANA levels 2 and 3 DEs introduced into some (possibly all) NEs/NFs of the Radio Access network. Figure 19: Network OAM protocols (Courtesy of ETSI GR IPE 005 [i.65]) Access Aggregation Core gNB gNB CSG gNB VLAN L3VPN on SRv6-BE Core Data Center BS BS L AMF UPF S CSG Pre- AGG Pre- AGG AGG AGG PE PE L S eBGP (e.g. option A, C) VLAN RR RR RR RR Server Farm VxLAN BH VRF BH VRF BH VRF N2, N3 X2, Xn 5GC VRF N2 N3 Internet GW N6 Pubic VRF Public VRF 5GC VRF 5GC VRF Access Aggregation Core gNB gNB CSG gNB Core Data Center BS BS L VM VM S CSG Pre- AGG Pre- AGG AGG AGG PE PE L S RR RR RR RR Server Farm BFD Y.1731 ICMP Ping / Traceroute Seamless BFD BFD TWAMP TI-LFA BFD TWAMP TI-LFA BFD TWAMP TI-LFA BFD ICMP Ping Traceroute ETSI ETSI TR 103 858 V1.1.1 (2026-03) 39 Figure 20 presents the Evolution of the IPv6-based 5G transport architecture described in ETSI GR IPE 005 [i.65]. The impact of introducing GANA Autonomics into this architecture scenario is as follows: • There are GANA DEs that are responsible for autonomically managing and orchestrating forwarding related protocols such as SRv6 (in particular the Forwarding-DE can be implemented to manage and orchestrate protocols SRv6 the other forwarding protocols; • The transport network would have a GANA KP associated with it instantiated and with possibility to have GANA levels 2 and 3 DEs introduced into some (possibly all) NEs/NFs of the transport network; • Instantiation of GANA onto a Data Centre (DC) physical network infrastructure follows the approach described in ETSI TR 103 404 [i.5] and if the DC is a virtualized one then the instantiation of GANA onto such virtualized DC network follows approach described in ETSI TR 103 473 [i.4]; • The Radio Access network part would have a GANA KP associated with it instantiated and with possibility to have GANA levels 2 and 3 DEs introduced into some (possibly all) NEs/NFs of the Radio Access network. Figure 20: Evolution of the IPv6-based 5G transport architecture (Courtesy of ETSI GR IPE 005 [i.65]) NOTE 2: For further study: Reference Architecture Scenarios that consider "IPv4 as a Service" in the IPv6-Only based 5G & Beyond Networks. 7 GANA Autonomic Management & Control (AMC) for IPv6 Protocols; IPv6 Capabilities that enable to Design & Build Autonomic 5G Networks and Services 7.1 Overview on GANA Autonomic Management & Control (AMC) of IPv6 Protocols in E2E 5G Networks, with consideration for Use Cases of AI/ML in the AMC Figure 21 presents an expanded view of the GANA node structure, the Decision Plane and Control Plane views and example assignments of DEs to some protocols, stacks and mechanisms as Managed Entities (MEs), that can be applied for a case of a GANA Node running IPv6 Protocols as Managed Entities (MEs). NOTE: More details on this can be found in ETSI GS AFI 002 [i.12]. Access Aggregation Core gNB gNB CSG gNB VLAN Core Data Center BS BS L VM VM S CSG Pre- AGG Pre- AGG AGG AGG PE PE L S Server Farm VLAN RR RR RR RR SRv6 (based on BGP EPE, or PCEP…) EVPN/ELINE/LxVPN based on E2E SRv6 ETSI ETSI TR 103 858 V1.1.1 (2026-03) 40 Figure 21: Expanded view of the GANA node structure, the Decision Plane and Control Plane views and example assignments of DEs to some protocols, stacks and mechanisms as Managed Entities (MEs) Figure 22 presents the interworking of Automated Management and Autonomic Management through the GANA Operations Procedures, and this framework described in ETSI TS 103 195-2 [i.2] on how the Autonomated Management Framework with Profiles is expected to work should be considered when deploying GANA autonomics onto the IPv6 based 5G network too. ETSI ETSI TR 103 858 V1.1.1 (2026-03) 41 Figure 22: The Interworking of Automated Management and Autonomic Management through the GANA Operations Procedures 7.2 IPv6 Capabilities that enable to Design and Build Autonomic 5G Networks and Services IPv6 Capabilities that enable to Design and Build Autonomic 5G Networks and Services have been started by the Seventh framework programme (FP7) of the European Community (EC) for research and technological development and demonstration activities [i.2] and IETF work such as work on ANIMA Protocols [i.60]. Research Projects like the European Commission (EC) funded FP7 Project EFIPSANS [i.59] carried out research on IPv6 capabilities that enable to design and build autonomic networks and services. EFIPSANS stands for: Exposing the Features in IP version Six (IPv6) Protocols that can be exploited/extended for the purposes of designing/building Autonomic Networks and Services. The EC funded FP7 EFIPSANS carried out the following study and produced results of relevance to the subject. EFIPSANS Project's main results covered the following aspects: 1) EFIPSANS Project examined and documented a number of the "existing" core IPv6 Features exploitable for autonomic networking (advanced Self-Managing Network Features) [i.43], [i.44], [i.53] and [i.62]. ETSI ETSI TR 103 858 V1.1.1 (2026-03) 42 2) EFIPSANS Project came up with some proposals on Extensions to IPv6 (IPv6++) that may be developed along the path to the Self-Managing Networks of the future [i.43], [i.44], [i.48] and [i.62]. EFIPSANS Project findings are that IPv6 offers a lot of rich communication features and extensible communication possibilities beyond what is available in IPv4. The following features in IPv6 can be considered as enablers for designing large-scale networks in which the basic attributes of scalability and some automated discovery and auto-configuration are required as enablers for more advanced autonomic/self-managing network behaviours: • Neighbour Discovery (ND); • auto-Configuration; • support for dynamic network re-numbering; • improved routing mechanisms; • improved Quality of Service (QoS) handling; • improved transport efficiency; • improved security; • flexibility for protocol extensions; • advanced addressing schemes and route aggregation; • true End-to-End communication; • concepts for realizing "locator/identifier split"; • Bootstrapping Mechanisms, etc. In EC funded EFIPSANS Project, some ideas on Extensions to IPv6 emerged and were developed: • As draft IPv6 Extension Headers (new IPv6 protocols that complement existing IPv6 protocols); • Newly added protocol Options in the Extension Headers that support the notion of Options; • Extensions to the "management interfaces" of some protocols for ensuring enriched access to the protocols and autonomic management and control of the protocols by associated Decision-Making-Elements (DEs), and network architectural extensions such as cross-layering, etc. • Examples of IPv6 protocol Extensions for self-managing networks innovated by EFIPSANS Project [i.59] include the following: - ICMPv6++ [i.61] for advanced control information exchange for use in DE-to-DE communications; - ND++ [i.43], [i.44] for advanced Auto-Discovery; - DHCPv6++ [i.43], [i.44] for advanced Auto-Discovery and Auto-Configuration as a protocol for providing ONIX Services; - PMIPv6++ [i.56]: This was not an extension to the protocol itself but to configurable and controllable parameters on the management interface of the protocol that DE can use in autonomic management and control of the PMIPv6 protocol; - IPv6 Extension Header for carrying advanced QoS Options, Other types of Newly added Options, some recommendations for Extensions to protocols like OSPFv3, and some newly suggested Extension Headers, etc. Examples of protocols put forward in IETF and are of relevance to consider for GANA autonomics in IPv6 based networks: 1) Autonomic IPv6 Edge Prefix Management in Large-Scale Networks, IETF RFC 8992 [i.69]. 2) GeneRic Autonomic Signalling Protocol (GRASP), IETF RFC 8990 [i.70]. ETSI ETSI TR 103 858 V1.1.1 (2026-03) 43 3) ICMPv6 based Generic Control Protocol (IGCP) [i.61] is meant to be used in DE-to-DE coordinations. 4) There may be other IPv6 protocols or new extensions in IETF made as RFC Drafts proposals that need to be studied. 8 Framework for Implementing Autonomic/Autonomous IPv6 based 5G Networks, powered by GANA Multi-Layer AI/ML & Multi-Layer AMC and IPv6 Capabilities 8.1 Overview about the Framework defined by the present document The following is a summary of what constitutes the Framework defined by the present document. This summary helps provide insights on the Framework's key aspects for considerations by implementers of GANA Multi-Layer AI/ML & Multi-Layer AMC in IPv6 based 5G Networks. The Framework consists of the following key aspects summarized below: Aspects described in the earlier clauses of the present document: • Principles for Autonomic/Autonomous Networking (AcN/AN) and Autonomic Management & Control (AMC), and Enablers. • Implementing the GANA Framework for Multi-Layer Autonomics and Multi-Layer AI/ML in IPv6 based network (e.g. an E2E 5G Network). Examples of DEs for consideration include QoS-management-DE, Security-management-DE, Mobility-management-DE, Fault-management-DE, Resilience & Survivability-DE, Service & Application management-DE, Forwarding-management-DE, Routing-management-DE, Monitoring-management-DE, Generalized Control Plane management-DE. • Integration of the GANA Knowledge Plane (KP) with various management and control systems through which the Knowledge Plane can selectively program the network, and KP integration with Event Sources, Data Sources and Info/Knowledge Sources. • Federated AMC by GANA KP Platforms and also Federation of low level Autonomics. • Use Cases for AI/ML and Autonomics in E2E IPv6 based 5G Networks in general; and Mappings to GANA DEs that help implement particular Use Case. • IPv6-Only based E2E 5G Networks: E2E Aspects of IPv6 in 5G and Reference Architecture Scenarios for Consideration; Implications on GANA Autonomics. • GANA Autonomic Management & Control (AMC) for IPv6 Protocols; IPv6 Capabilities that enable to Design & Build Autonomic 5G Networks and Services. Aspects described in the subsequent clauses of the present document: • GANA Multi-Layer Autonomics & AI/ML in IPv6-Only based 5G E2E Reference Architecture Scenarios, with Consideration of the Example Autonomics Use Cases. • DEs to MEs Mappings, and Autonomic Management & Control of IPv6 Protocols by GANA DEs. • GANA for Access Network (Fixed Access, RAN, Other Access Networks). • GANA Autonomics for Multi Layer Transport SDN Architecture. • GANA for 5G Service Based Architecture (SBA). • GANA Autonomics for MEC Architecture. ETSI ETSI TR 103 858 V1.1.1 (2026-03) 44 • Federation of the GANA KPs for RAN, MEC, Transport Network, Core Network, and IP Multimedia Subsystem (IMS) Layer. 8.2 GANA Multi-Layer Autonomics & AI/ML in IPv6-Only based 5G E2E Reference Architecture Scenarios, with Consideration of the Example Autonomics Use Cases 8.2.1 DEs to MEs Mappings, and Autonomic Management & Control of IPv6 Protocols by GANA DEs Table 1 below provides a guidance on DE-to-ME Mappings Table concerning which DE is responsible for autonomic management and control of specific types of Managed Entities (MEs). Following the GANA implementation guide this means in an IPv6 network, the MEs that are IPv6 specific and those that are not IPv6 specific should be assigned to specific DEs (in a 1-ME to 1-DE relationship) using Table 1 as a guide before designing and implementing the DEs in the GANA Knowledge Plane Level and in certain NEs/NFs. For example, the Routing Management DE's MEs are routing protocols and mechanisms as illustrated on Figure A.3 3. Each DE should employ AI/ML Algorithms in the autonomic management and control of its MEs (including IPv6 Protocols accordingly) using their Managed Objects and management methods that a DE can employ, while the DE performs the autonomic management and control of its MEs in reaction to detected or predicted situations, changes in network optimization or adaptation objectives, and in collaboration with other DEs as may be necessary. Table 1: Generic Table for the Mapping of DEs to their associated Types of Managed Entities (MEs) NOTE 1: More details in ETSI TS 103 195-2 [i.2]. NOTE 2: Autonomic management and control of IPv6 protocols, stacks and mechanisms as so-called Managed Entities (MEs) at GANA's lowest level/layer, is based on the assignment of specific IPv6 protocols and mechanisms to specific Decision Elements (DEs) that autonomically manage and regulate/control the behaviour of the different MEs. Network-Level DEs S Node-Level DEs Function-Level DEs Protocols and Mechanisms as Managed-Entities (MEs) Examples of protocols and Mechanisms that are mapped as MEs GANA NODE NET_LEVEL_SEC_M_DE Security Protocols, Algorithms and Mechanisms Certificates/Passwords Algorithms, Hash Algorithms, Encryption Algorithms, Access Control Mechanisms, Trust Mechanisms, Denial of Service (DoS) Detection/Prevention algorithms/mechanisms, Signature based intrusion detection mechanisms, etc. NODE_LEVEL_SEC_M_DE NET_LEVEL_FM_DE NODE_LEVEL_FM_DE Fault Detection Mechanisms, Fault Isolation/Localization/Diagnosis Mechanisms, Fault Removal Mechanisms Active Probing mechanisms, Bi-Directional Forwarding Detection (BFD protocol) for link failure detection, Self- test/diagnose functions, rebooting, reloading, automated module replacement mechanisms, etc. NET_LEVEL_RS_DE NODE_LEVEL_RS_DE Proactive and Reactive Resilience Mechanisms, Survivability Strategies and Algorithms, Restoration and Protection Mechanisms Node Resilience mechanisms, and Network Resilience mechanisms, etc. NODE_LEVEL_AC_DE Neighbour Discovery Protocols/Mechanisms and Network Discovery Mechanisms Neighbour Discovery Protocol (NDP), Secure Neighbour Discovery Protocol (SEND), etc. NET_LEVEL_RM_DE NODE_MAIN_DE FUNC_LEVEL_RM_DE Routing Protocols and Mechanisms OSPF, BGP, RIP, ISIS, etc. NET_LEVEL_FWD_M_DE FUNC_LEVEL_FWD_M_DE Layer-3 Forwarding Protocols and Mechanisms, Layer- 2.5-Fowarding, Layer-2-Fowarding, Layer-3-Switching, Layer-2-Switching, etc. IPv4/IPv6 Forwarding Engine, Multi-Protocol Label Switching (MPLS), etc. NET_LEVEL_QoS_M_DE FUNC_LEVEL_QoS_M_DE QoS Protocols and Mechanisms Packet classifier, Packet Marker, Queue Management, Queue Scheduler, RSVP, etc. NET_LEVEL_MOM_DE FUNC_LEVEL_MOM_DE Mobility Management Protocols and Mechanisms Mobility Support in Internet Protocol Version 6 (MIPv6), Datagram Congestion Control Protocol, Mobile Stream Control Transmission Protocol, Site Multi-homing by IPv6 Intermediation, Proxy-Mobile-IP, Mobility-Management User- Equipment Managed-Entity, Measurement-Report-Function Managed-Entity, Candidate-Access-Router-Discovery mechanism, Fast Handover Scheme, Policy Control and Charging Rules Function mechanism, etc. NET_LEVEL_MON_DE FUNC_LEVEL_MON_DE Monitoring Protocols, Mechanisms and Tools IPFIX data collection and dissemination mechanisms, SNMP data collection and dissemination mechanisms, NETFLOW data collection and dissemination mechanisms, Protocol Analysers, Packet Trace creation and dissemination mechanisms. Effective and Available Bandwidth Estimation mechanisms, IPv6 hop-by-hop options for intrinsic monitoring, etc. FUNC_LEVEL_SM_DE Services and Applications Orchestration of services, service-discovery, interpretation of service and application requirements at run-time and requesting the network layer to behave in a service/application-aware manner, realizing a control-loop over the services/applications as its Managed Entities (MEs), collaboration with other DEs of responsible of autonomic management of the network layer protocols in order to realize collaborative self-adaptation on both the service-layer and the network-layer. NOTE: There are other DEs that may have not been included in the Table 3 and implementers should take them into account based on their descriptions provided in the present document. Such DEs include Network-Level-Generalized Control Plane-Management-DE (NET-LEVEL-GCP_M_DE), Function-Level-Generalized Control Plane- Management-DE (FUNC-LEVEL-GCP_M_DE), Network Level End-to-End “end-user oriented” Service and Applications Management (NET_LEVEL_E2E_Service_M). ETSI ETSI TR 103 858 V1.1.1 (2026-03) 45 8.2.2 GANA for Access Network (Fixed Access, RAN, Other Access Networks) Figure 23 presents GANA for the RAN as represented by C-SON and D-SON for traditional RAN, and by a combination of RAN Intelligent Controllers (RIC) and rApps/xApps and dApps in the case of the Open RAN (O-RAN) Alliance Architecture, with consideration that the GANA KPs for each network segment should be federated for E2E Federated Autonomic Management and Control (AMC). ETSI ETSI TR 103 858 V1.1.1 (2026-03) 46 Figure 23: GANA for the RAN as represented by C-SON and D-SON for traditional RAN, and by a combination of RICs and rApps/xApps and dApps in the case of the O-RAN Alliance Architecture, with consideration that the GANA KPs for each network segment should be federated for E2E Federated AMC ETSI ETSI TR 103 858 V1.1.1 (2026-03) 47 KP DE (QoS DE) can be used to share QoS information across Radio, Transport, Core domains of the network to manage e2e QoS of all the network domains. NOTE: GANA for Fixed Access is defined in ETSI TR 103 473 V1.1.2 [i.4] and BroadBand Forum (BBF) oneM2M TR-436 [i.68]. |
7470f1226238696862acc2f2b74c08a3 | 103 858 | 8.2.3 GANA Autonomics for Multi Layer Transport SDN Architecture | Figure 24: Integration of the GANA Knowledge Plane (KP) Platform with SDN Controllers for Multi-Layer Transport SDN Network Figure 25 presents Integration of the GANA Knowledge Plane (KP) Platform with OSS/BSS, E2E Service Orchestrator, Domain Orchestrators, SDN Controllers for Multi-Layer Transport SDN Network, and Test Access Points (TAPs) and Switched Port Analyser (SPAN) Visibility architectures for Probing and Performance and Fault Management of the Transport Network. ETSI ETSI TR 103 858 V1.1.1 (2026-03) 48 Figure 25: Integration of the GANA Knowledge Plane (KP) Platform with OSS/BSS, E2E Service Orchestrator, Domain Orchestrators, SDN Controllers for Multi-Layer Transport SDN Network, and TAP and SPAN Visibility architectures for Probing and Performance and Fault Management of the Transport Network Figure 26 presents GANA Multi-Layer (Multi-Level) Autonomics for Multi-Layer Transport Network. ETSI ETSI TR 103 858 V1.1.1 (2026-03) 49 Figure 26: GANA Multi-Layer (Multi-Level) Autonomics for Multi-Layer Transport Network |
7470f1226238696862acc2f2b74c08a3 | 103 858 | 8.2.4 GANA for 5G Service Based Architecture (SBA) | Regarding GANA for 5G SBA Architecture, the three levels of GANA DEs hierarchy apply, namely GANA levels 2&3 that can be introduced into Network Functions (or Services in the case of the SBA) and GANA level (network level). However, GANA Levels 2 and 3 DEs should be implemented as micro services in SBA. The GANA Knowledge Plane (KP) for the SBA should be implemented as overlay on top of the 5G SBA and made to integrate with Analytics Functions or Services as illustrated in the figure in clause 4 on "Integration of the GANA Knowledge Plane (KP) with various management and control systems through which the Knowledge Plane can selectively program the network; and KP integration with Event Sources, Data Sources and Info/Knowledge Sources". As described in clause 4.3, functions such as the Network Data Analytics Function (NWDAF) [i.8] and the Management Data Analytics Service (MDAS) [i.9] need to be integrated with KP Platform so that events and KPIs data from the functions can be used by KP DEs in their autonomic operations. DEs of the KP Platform should be implemented as micro services too. NOTE: Figure 1 in clause 4 on GANA instantiation onto the 5G core reference architecture (ETSI TS 123 501 [i.22]) with functional distribution in a 3-levels DCs structure, offers useful insights. |
7470f1226238696862acc2f2b74c08a3 | 103 858 | 8.2.5 GANA Autonomics for MEC Architecture | Figure 27 presents GANA Autonomics for MEC Architecture. It shows the GANA Levels where DEs can be introduced into the architecture. NOTE: The lower level GANA DEs introduced in some components of the architecture may be limited to GANA Node-level DEs (GANA Level 3 DEs such as Auto-Configuration DE, Fault- Management DE, Security Management-DE, etc.). ETSI ETSI TR 103 858 V1.1.1 (2026-03) 50 Figure 27: GANA Autonomics for MEC Architecture 9 Executing PoCs Program on the Framework for Implementing Autonomic/Autonomous IPv6 based 5G/6G Networks powered by GANA, AI, and IPv6 This clause describes the steps that should be pursued in running a Proof of Concept (PoC) on the Framework for Implementing Autonomic/Autonomous IPv6 based 5G and Beyond Networks, powered by GANA Multi-Layer AI & Multi-Layer AMC and IPv6 Capabilities. The PoC can serve the purpose of guiding the industry on how to implement the standards that underpin the PoC and provide feedback to TC INT on any implementation challenges and interoperability issues so that the feedback can be used to improve and evolve GANA related standards or to create new standards in TC INT or other Standardization Groups with competence on the related technical topics. PoC Scope: Framework (presented by the present document) for Implementing Autonomic/Autonomous IPv6 based 5G/6G and Beyond Networks powered by ETSI GANA Multi-Layer Autonomics & Multi-Layer AI/ML-Algorithms and IPv6 Capabilities (including Segment Routing). The Reference work would be ETSI TR 103 858 (the present document): • Objectives of a PoC (among multiple PoCs that may be targeted as deriving from the Framework that can be considered to start with), and Expected Output: 1) Implement a part of the Framework (Guide) described by the present document (ETSI TR 103 858) on Implementing Autonomic/Autonomous IPv6 based 5G Networks, by leveraging the ETSI GANA Multi- Layer AI / Multi-Layer Autonomic Management and Control Model and IPv6 Capabilities & Extensions that enable to Build Autonomic Networks. The Framework prescribes how to introduce software components called Autonomic Functions (ETSI GANA Decision-making-Elements (DEs)), e.g. Autonomic-QoS-Management-DE, Autonomic-Security-Management-DE, etc., in the IPv6 based 5G Architecture and its associated Management and Control Architecture. The DEs and their associated Algorithms (including analytics, optimization and AI/ML algorithms) are meant to drive control-loops within Network Functions of the 5G network infrastructure and/or drive control-loops at the higher level of abstraction for self-management functionality that is positioned within the outer Management and Control realm of a 5G Network Infrastructure - within a platform called the GANA Knowledge Plane (KP) Platform. The selected part of the Framework that can be targeted by the first PoC is one that involves Adaptive Autonomic provisioning and tear-down of IPv6/SRv6 based Network Slices and Segment Routing in the SDN Programmable Multi-Layer Transport Network by the GANA Knowledge ETSI ETSI TR 103 858 V1.1.1 (2026-03) 51 Plane for the Multi-Layer Transport Network as illustrated in Figure 8 and NOTE: Multi-Layer aspect in transport networks usually implies IP and Optical Level. Figure 10. The Adaptive Autonomic provisioning and tear-down of Slices is driven by various factors that include new SLAs and changes, and SLA and security assurance in the advent of challenges observed in the transport network that include faults/errors/failure manifestations, security problems and certain workload scenarios encountered, and other factors. 10 Ongoing PoCs Program on GANA in ETSI 5G PoC Implementations by the Industry The link to the ETSI INT PoC program is the following https://intwiki.etsi.org/index.php?title=Accepted_PoC_proposals. |
7470f1226238696862acc2f2b74c08a3 | 103 858 | 11 Conclusion and Further Work | DE algorithms are not subject to standardization as they provide for the space for innovation and DE and Algorithm supplier differentiations. Examples of Autonomic Functions (i.e. GANA DEs) are: QoS-management-DE, Security-management-DE, Mobility-management-DE, Fault-management-DE, Resilience & Survivability-DE, Service & Application management-DE, Forwarding-management-DE, Routing-management-DE, Monitoring-management-DE, Generalized Control Plane management-DE. Some aspects of the present document about interoperability with legacy networks and multivendor systems (e.g. European Advanced Networking Test Center (EANTC) SRv6 interoperability test [i.64]), as well as the reference points needed for new use cases such as fault, configuration and monitoring management (e.g. autodiscovery of the network) are in need for further investigation in future releases. ETSI ETSI TR 103 858 V1.1.1 (2026-03) 52 Annex A: Supplementary Information TC INT AFI WG is a standardization group that has strong competence in the area of Autonomic Management and Control (AMC) standards and has established various liaisons with various key SDOs/Fora on the subject of introducing autonomics in their network architectures in standardized way. Figure A.1 below shows the various liaisons established between TC INT AFI WG and key SDOs/Fora as shown below, and the kinds of deliverables produced as a result of the various collaborations established. Figure A.1 As described in ETSI TS 103 195-2 [i.2] and NGMN's 5G End-to-End Architecture document [i.10], the ETSI GANA Model is a Hybrid Model for realizing the AMC paradigm and is very much compatible with and embraces the Hybrid Self-Organizing Network (SON) Model (consisting of Distributed-SON and Centralized-SON complementing each other and made to interwork together by way of C-SON policy-controlling D-SON). The GANA Model applies not only to designing and implementing AMC for Radio Access Network (RAN) but is a generic model that can be applied to other network segment types such as Cable Access, Fixed Network Access, MEC(Multi-Access Edge Computing), X-Haul Transport and Core Network as illustrated in various GANA instantiations onto target architectures such as GANA in BBF architecture scenarios (ETSI TR 103 473 [i.4]) and GANA in 3GPP Backhaul and EPC Core Network (ETSI TR 103 404 [i.5]). Recommendation ITU-T Y.3324 [i.71] also provides insights on the AMC paradigm in IMT-2020 and how to use the ETSI GANA Model to realize AMC in IMT-2020. There are other deliverables produced by INT AFI WG on the subject of introducing GANA autonomics in network architectures (including GANA implementation onto Heterogeneous Wireless Access Technologies using Cognitive Algorithms (ETSI TR 103 626 [i.66])). AFI WG work on introducing GANA autonomics in various network architectures and their associated management and control architectures continues. ETSI ETSI TR 103 858 V1.1.1 (2026-03) 53 Figure A.2 presents an illustration of the Interaction between a DE in the Knowledge Plane (KP) level with a DE implemented in NE/NF. Figure A.2: Illustration of the Interaction between a DE in the Knowledge Plane (KP) level with a DE implemented in NE/NF Main Decision Element of the Node (Node-DE) Objectives, Policies from a higher level (network-level-DE) Decision Element of an abstracted Network Function e.g. Routing Main Decision Element of the Node (Node-DE) Objectives, Policies from a higher level (network-level-DE) Decision Element of an abstracted Network Function e.g. Routing Decision Element intrinsic to a Routing Protocol e.g. OSPF Decision Element intrinsic to a Routing Protocol e.g. OSPF Peers Peers Peers Node X Node Y Decision Element intrinsic to a Routing Protocol e.g. OSPF Decision Element of an abstracted Network Funtion e.g. QoS Management Example interaction between Sibling Decision Elements GANA’s lowest level/ layer MEs: Protocols, Protocol Stacks, Services/Applications and fundamental Mechanisms NOTE: All the Types of DE Interfaces depicted illustrate the need for „node/device-intrinsic management“ and „network-intrinsic management or in-network management“ in Self-Managing Future Networks ETSI ETSI TR 103 858 V1.1.1 (2026-03) 54 Figure A.3 presents an Illustration of the interworking of fast control-loop and slower control-loop for routing management (can be applied both to IPv6 and IPv4 environments). NOTE: More details on this subject can be found in ETSI White Paper No.16 [i.1]. Figure A.3: Illustrating the interworking of fast control-loop and slower control-loop for routing management (can be applied both to IPv6 and IPv4 environments) ETSI ETSI TR 103 858 V1.1.1 (2026-03) 55 Annex B: Bibliography • 5G security - Package 3: Mobile Edge Computing / Low Latency / Consistent User Experience: by NGMN Alliance: 20 February 2018, by NGMN 5G security group. • IBM White paper: "An architectural blueprint for autonomic computing", MAPE-K, June 2005. • Andrew Lerner: "AIOps Platforms", Gartner® Blog, August 2017. • N. Miloslavskaya, A. Tolstoy: "Big Data, Fast Data and Data Lake Concepts", Elsevier Procedia Computer Science, vol. 88, pp. 300-305, October 2016. ETSI ETSI TR 103 858 V1.1.1 (2026-03) 56 History Version Date Status V1.1.1 March 2026 Publication |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 1 Scope | The present document provides requirements that are specific enough to define the desired security outcomes, but flexible enough that there can be innovation and different ways for how they can be achieved. Whilst it is initially targeted towards the Telecoms Sector, the principles are designed to be industry agnostic. The present document covers system integration and follows on from ETSI TS 103 994-1 - Devices [1] and ETSI TS 103 994-2 - Connectivity [2]. This series of documents will cover different aspects of PAWs that can work in conjunction with each other to meet the needs of the overall system architecture and the relevant security aims. |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 2 References | |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 2.1 Normative references | References are either specific (identified by date of publication and/or edition number or version number) or non-specific. For specific references, only the cited version applies. For non-specific references, the latest version of the referenced document (including any amendments) applies. Referenced documents which are not found to be publicly available in the expected location might be found in the ETSI docbox. NOTE: While any hyperlinks included in this clause were valid at the time of publication, ETSI cannot guarantee their long-term validity. The following referenced documents are necessary for the application of the present document. [1] ETSI TS 103 994-1 (V1.1.1): "Cyber Security (CYBER); Privileged Access Workstations; Part 1: Physical Device". [2] ETSI TS 103 994-2 (V1.1.1): "Cyber Security (CYBER); Privileged Access Workstations; Part 2: Connectivity". |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 2.2 Informative references | References are either specific (identified by date of publication and/or edition number or version number) or non-specific. For specific references, only the cited version applies. For non-specific references, the latest version of the referenced document (including any amendments) applies. NOTE: While any hyperlinks included in this clause were valid at the time of publication, ETSI cannot guarantee their long-term validity. The following referenced documents may be useful in implementing an ETSI deliverable or add to the reader's understanding, but are not required for conformance to the present document. [i.1] Department for Digital, Culture, Media and Sport: "Telecommunications Security Code of Practice". ETSI ETSI TS 103 994-3 V1.1.1 (2026-01) 7 |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 3 Definition of terms, symbols and abbreviations | |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 3.1 Terms | For the purposes of the present document, the following terms apply: Privileged Access Workstation (PAW): appropriately secured device that enables an admin user to access data and/or make changes to security critical functions via a management plane NOTE: This is defined in [i.1]. |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 3.2 Symbols | Void. |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 3.3 Abbreviations | For the purposes of the present document, the following abbreviations apply: IAM Identity and Access Management OS Operating System OT Operational Technology PAM Privileged Access Management PAW Privileged Access Workstation PDF Portable Document Format SOC Security Operations Centre VPN Virtual Private Network |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 4 PAW design considerations and integration | |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 4.1 PAW design considerations | |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 4.1.1 Introduction | The deployment of a Privileged Access Workstation (PAW) solution shall account for the impact on user workflows. The design process shall incorporate input from end users as well as risk owners, ensuring that operational realities are reflected in the solution. Assumptions regarding role execution shall not replace direct engagement with users. To minimize adoption challenges, the organization should: • conduct user research and usability testing throughout the design and implementation phases, with emphasis on early-stage design; • perform regular reviews of the solution design to accommodate evolving requirements. |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 4.1.2 Factors to consider during Commissioning and Procurement | Failure to define accurate requirements at this stage may result in procuring or developing an unsuitable solution. The organization should consider: • current processes: what functions effectively and what does not; • role-specific tasks and operational conditions; • actual work practices versus prescribed processes; ETSI ETSI TS 103 994-3 V1.1.1 (2026-01) 8 • use of diverse information sources to improve understanding; • scope and resourcing of usability activities to ensure adequate support; • engagement of suitably qualified and experienced personnel for usability work; • avoiding reliance solely on user-stated preferences (to prevent designing a "faster horse"); • avoiding reliance solely on technical excellence (which may result in an unused "perfect" control); • identification of key stakeholders, including system owners, administrators, installers and end users. A solution that fails to meet user needs is likely to result in workarounds or shadow IT, thereby increasing organizational risk. The organization shall establish a continuous learning and feedback mechanism to identify process deficiencies and drive iterative improvements. |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 4.2 Identify high-risk accesses | PAWs may be deployed for all privileged access scenarios; however, their use is most critical for high-risk accesses. An access shall be considered high risk if: • the potential impact of compromise is severe; or • the systems protected by such access are likely to be targeted by a capable threat actor. High-risk accesses represent a subset of privileged access. A system or device shall be classified as high risk where existing security controls cannot adequately mitigate the consequences of misuse. This includes, but is not limited to: • accesses that can directly modify or bypass critical security controls; • accesses that can expose sensitive data; • accesses where compromise may result in significant organizational impact. EXAMPLE: An attack on a trusted component such as a certificate authority server may compromise system integrity and be difficult to detect or remediate. To identify privileged and high-risk accesses, the organization should assess the potential actions of a threat actor following compromise, including: • the use of any discovered credentials; • the presence of connectivity to other systems, whether physical or network-based; • the possibility of escalation to internal systems with weak security controls, which may serve as stepping stones for further attacks. The organization should refer to threat modelling guidance to support this assessment. Entities operating in high-threat environments, such as those within Critical National Infrastructure (CNI), shall assume that highly skilled adversaries may conduct multi-stage attacks following an initial compromise. In such cases, PAWs should be applied to a broader range of privileged accesses as part of a layered defence strategy. Defence-in-depth increases the cost and complexity of an attack, thereby reducing its likelihood of success. It is important to note that PAWs operate under the assumption that an authenticated user is trusted; therefore, they do not inherently mitigate insider threats. However, PAWs support broader access management, monitoring, and auditing controls, which contribute to insider risk mitigation. |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 4.3 PAM Integration | Prior to the deployment of a PAW, the organization shall establish a clear understanding of the operational need and associated risk scenarios. The implementation of a PAW shall form part of a risk-based approach that identifies potential threats and defines the required defensive measures. ETSI ETSI TS 103 994-3 V1.1.1 (2026-01) 9 Privileged Access Management (PAM) is a core component of cybersecurity that addresses the protection of privileged accounts and associated assets. The use and deployment of PAWs shall be considered within the context of the organization's overall PAM strategy. When defining the PAM strategy, the organization should evaluate the security benefits of PAW solutions, which include: • Reduction of attack surface: PAWs are effective in mitigating the risk of device compromise by external threat actors. • Prevention of common attack vectors: PAWs provide strong protection against phishing and similar attacks. • Mitigation of accidental misuse: PAWs reduce the likelihood of users unintentionally installing malicious software. • Containment of lateral movement: PAWs limit the ability of attackers to pivot from compromised devices, reinforcing the need to minimize interaction between PAW activities and general business operations. PAW devices may also support and enhance other Identity and Access Management (IAM) controls. The adoption of architectural models such as Zero Trust does not eliminate the requirement for PAWs. Certain risks can only be mitigated through the use of highly trusted devices. A PAW shall serve as a foundational element to maintain trust in technical controls and overall security posture. |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 4.4 Cross Domain Dataflow | |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 4.4.1 Introduction | When implementing an import/export mechanism for a PAW environment, the organization shall begin by identifying the types of data that require transfer between enterprise and PAW environments. Complex data formats (e.g. Microsoft Word, PDF) present higher security risks and are more difficult to sanitise than structured formats (e.g. XML, JSON). The organization should minimize data transfers to essential content only and, where feasible, convert data into simpler, lower-risk formats. |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 4.4.2 Data Transfer Solution Requirements | The data transfer solution shall: • generate a complete audit trail for all data entering or leaving the PAW environment; • require user authentication prior to any transfer; • ensure that only approved and authorized content is exported; • automate transfers to predefined, pre-configured endpoints, prohibiting export to arbitrary destinations; • inspect and scan all data for malicious content, particularly for imports into the PAW environment; • validate data structure where appropriate to maintain integrity. |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 4.4.3 Threat Context Considerations | For high-threat environments, data control solutions should, where feasible, be implemented in hardware. For lower-threat contexts, software-based controls combined with network boundary restrictions may be acceptable. The organization should refer to their National Technical Authority on secure data import/export patterns for additional implementation details. ETSI ETSI TS 103 994-3 V1.1.1 (2026-01) 10 |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 4.5 Legacy Technology | |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 4.5.1 Introduction | The organization shall avoid running obsolete software or Operating Systems (OS) on PAWs. Where this is not feasible for operational continuity - primarily in Operational Technology (OT) environments - obsolete applications shall be isolated and segregated from the PAW environment. |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 4.5.2 Preferred Approach | The organization shall engage with the vendor of the obsolete application or OS to identify alternative solutions, such as: • upgrading to a supported version; • porting the application to a modern OS; • implementing containerization or virtualization strategies. |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 4.5.3 Virtualization and Isolation Controls | If obsolete products remain necessary and no viable alternatives exist, the organization shall: • use virtualization to segregate obsolete software from the PAW; • restrict access to obsolete applications to only those users who require it; • document obsolete products and associated users as technical debt, and maintain a roadmap for migration to modern solutions. The organization shall treat any obsolete OS as insecure by default. Security functionality provided by the obsolete OS shall not be relied upon. Additional external security controls shall be implemented. |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 4.5.4 Virtualization Security Requirements | Each obsolete OS instance shall have: • no direct network connectivity to the host machine; • no connectivity to other virtualized hosts (each instance shall operate on an isolated virtual network). A virtualized managed firewall appliance shall be pre-configured centrally: • PAW users shall not have the ability to modify firewall configurations or log into the appliance. • Any VPN configuration for the PAW running an obsolete OS shall be implemented at the firewall appliance, not on the obsolete OS. Where legacy virtual environments require connectivity to external services, an additional virtualized security boundary shall be implemented and centrally managed. PAW users shall not have the ability to modify this boundary. |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 4.5.5 Security Tooling Considerations | The organization shall assess the risk of deploying security tools (e.g. antivirus) on obsolete virtual machines, as these tools operate on vulnerable OS platforms and their results cannot be fully trusted. Additional external monitoring should be implemented to compensate for the limited effectiveness of on-host security tools. ETSI ETSI TS 103 994-3 V1.1.1 (2026-01) 11 |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 5 Initial Device | |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 5.1 Build in isolation | |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 5.1.1 Introduction | The initial configuration of a Privileged Access Workstation (PAW) solution shall prioritize security to prevent cross-contamination and maintain system integrity. The organization shall not build PAW systems from existing devices. Instead, PAWs shall be provisioned using new, clean devices sourced through a trusted and well-understood supply chain. |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 5.1.2 Single-Device and Initial Deployment Scenarios | In small-scale or single-device deployments, the initial device may serve as the sole PAW. To ensure compliance, this device shall adhere to all applicable lockdown policies. Typically, this device is used to provision the PAW management environment, establishing a clean and physically segregated network segment. This segment shall subsequently be expanded to include additional PAW devices and supporting services. |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 5.1.3 Multi-Device Deployments | Where multiple PAW devices are required, the initial device shall be integrated into the PAW Mobile Device Management (MDM) solution and enrolled as a PAW device once the MDM is operational. The initial device shall not be used for administrative tasks until all technical controls and lockdown policies are fully implemented. Following MDM configuration, the device shall be enrolled to ensure consistent policy enforcement across all PAW devices. |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 5.2 Secure your PAW Infrastructure | Once the Privileged Access Workstation (PAW) infrastructure has been deployed within an isolated environment, it shall be subject to a series of security and operational controls to ensure its integrity and compliance with organizational requirements. All systems shall be kept up to date through the application of relevant security patches, thereby reducing exposure to known vulnerabilities. Appropriate policy enforcement shall be applied across the PAW environment, ensuring consistent configuration and adherence to the principle of least privilege. The environment should be integrated with a centralized identity provider, and Multi-Factor Authentication (MFA) shall be enabled for all user accounts. The only exception to this requirement shall be the designated break-glass account, which shall be strictly controlled and used solely for emergency access. Comprehensive logging and monitoring shall be configured to capture authentication events, system changes, and access activity. These logs shall be forwarded to a secure, centralized logging solution and monitored continuously to detect and respond to any anomalous or unauthorized behaviour, thereby maintaining the security posture of the PAW infrastructure. |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 5.3 Scale with MDM / Zero touch deployments | Where a PAW solution comprises multiple devices, the organization shall ensure that security controls can be scaled effectively. This requires the use of a well-secured management platform, which shall be administered from a trusted system. The organization should ensure that all modifications and configuration changes to the PAW environment are consistent, reliable, and auditable. To achieve this, the use of Infrastructure as Code (IaC) is recommended. IaC enables: • automated provisioning and configuration of infrastructure, reducing the likelihood of human error; • simplified duplication of environments; ETSI ETSI TS 103 994-3 V1.1.1 (2026-01) 12 • streamlined updates and patching processes; • consistent compliance enforcement across the PAW estate. The organization shall maintain a unified view of device compliance across the entire PAW deployment and shall closely monitor configuration changes to verify that all modifications are authorized. |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 6 PAW backup plan | |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 6.1 PAW Resilience | |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 6.1.1 Introduction | Once implemented, a PAW solution shall be the exclusive method for performing high-risk privileged access within the organization. The PAW solution shall be designed with sufficient resilience to support both normal operations and failure scenarios. During the design phase, the organization shall assess: • the required level of resilience; • the operational impact of partial or complete PAW failure. The PAW solution shall remain accessible and available to authorized personnel when required. Its role in incident response and recovery shall be considered, including its function as a trusted device for emergency access using break-glass accounts. High availability reduces the likelihood of users resorting to non-PAW devices for emergency access. |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 6.1.2 Break-Glass Access Requirements | Break-glass accounts shall be exempt from technical enforcement controls to ensure availability during emergencies. Break-glass accounts shall, where possible, be accessed from a trusted PAW device due to the high-risk nature of these credentials. In exceptional circumstances where PAWs are unavailable and business-critical access is required, organizational policy may permit the use of alternative devices. |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 6.1.3 Security and Operational Controls | Activation of a break-glass account shall automatically trigger an alert for immediate investigation and be treated as a maximum criticality incident. Break-glass access shall only be used as a last resort and never for routine operations or remote access by third parties. Post-incident, the organization shall conduct a full investigation, including: • assessing whether trust in the PAW solution has been compromised; • determining if any systems require rebuilding to restore a known good state; • reviewing and updating security measures for break-glass accounts, including password changes; • evaluating opportunities to reduce reliance on break-glass accounts in future scenarios. |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 6.1.4 Credential Management and Testing | Break-glass credentials shall be stored securely, including maintaining a physical copy where appropriate. Access to credentials shall be restricted to authorized personnel and subject to monitoring and auditing. ETSI ETSI TS 103 994-3 V1.1.1 (2026-01) 13 Break-glass access shall be routinely tested to confirm functionality, including validation of alerting and incident escalation processes. |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 7 Protective Monitoring | |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 7.1 Monitoring Requirements | The monitoring solution shall provide visibility over: • the PAW device itself; • supporting systems, including configuration and change management platforms. Logging events shall be streamed to a secure log-processing system in near real-time. Protections shall be implemented to prevent tampering with logs on the device and within the log-processing system. Logs shall be immutable to ensure integrity. Where administrative users require privileged access to log collection or storage systems, such access shall be highly restricted and routinely audited. Where feasible, logs from PAW devices shall be transmitted directly to a central monitoring solution, such as a SOC. 7.2 Monitoring Configuration and Change Management Systems The organization shall monitor configuration and change management systems to maintain trust in the PAW solution. Alerts shall be generated for any configuration changes, enabling security teams to verify whether changes are authorized and expected. This is critical as unauthorized changes may re-enable functionality or introduce additional tooling, undermining PAW security. |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 7.3 Anomaly Detection | The organization shall implement anomaly detection for all uses of privileged identities. Additional logging should be enabled to capture actions performed on PAW devices, enhancing accountability and mitigating insider threats. Given the constrained nature of PAWs, anomaly detection shall identify any activity outside the expected operational scope as an indicator of misconfiguration or compromise. Where feasible, logs from PAW devices should be correlated with logs from target systems to detect anomalies. |
8c07a0652e2fc39ac1f6114bccf9b279 | 103 994-3 | 8 Threats and Mitigations | The present document addresses four primary threat vectors; however, these are not exhaustive, and additional risks may be covered within the points outlined here. It also considers the risk of lock-out and its mitigation through a Break- Glass procedure. While lock-out may not be a direct threat vector, being unable to access systems, whether due to accidental misconfiguration, service outage or malicious activity, can have a significant impact on recovery efforts. It is essential that any Break-Glass procedure is carefully designed to ensure access is always possible and that it is closely monitored for signs of malicious activity. The four main threats identified by MITRE are summarized in Table 1. ETSI ETSI TS 103 994-3 V1.1.1 (2026-01) 14 Table 1 Threat Vector Risk Mitigation and Effect Credential Access Credential Access consists of techniques for stealing credentials such as account names and passwords. Techniques used to get credentials include keylogging or credential dumping. Using legitimate credentials can give adversaries access to systems, make them harder to detect, and provide the opportunity to create more accounts to help achieve their goals. By designing and integrating PAWs alongside the PAM solution, credentials are safeguarded, only exposed when required, and regularly rotated by the PAM system. Additional mitigations previously outlined in ETSI TS 103 994-1 [1] and ETSI TS 103 994-2 [2], such as device lockdown and the principle of browse-down, further strengthen defence-in-depth measures. The combined effect is that stealing and successfully exploiting credentials becomes significantly more difficult when PAW and PAM are properly designed, integrated and implemented. Exfiltration Exfiltration consists of techniques that adversaries may use to steal data from your network. Once they have collected data, adversaries often package it to avoid detection while removing it. This can include compression and encryption. Techniques for getting data out of a target network typically include transferring it over their command-and- control channel or an alternate channel and may also include putting size limits on the transmission. Implementing a well-defined cross-domain solution with structured data flows makes systems significantly harder to compromise by reducing attack surfaces and enforcing controlled, secure interactions between domains. This approach also strengthens defence-in- depth by adding an additional layer of protection against lateral movement and data exfiltration. Lateral Movement Lateral Movement consists of techniques that adversaries use to enter and control remote systems on a network. Following through on their primary objective often requires exploring the network to find their target, then pivoting through multiple systems and accounts to gain access to it. Adversaries might install their own remote access tools to accomplish Lateral Movement or use legitimate credentials with native network and operating system tools, which may be stealthier. Building the PAW separately from other systems, applying security policies, and only connecting it once fully secured significantly reduces the risk of a threat actor laterally moving to the PAW or its network during the initial build. Furthermore, when all management interfaces are isolated within a dedicated management network that can only be accessed from a PAW, the ability to launch attacks is greatly diminished. Discovery / Reconnaissance Discovery consists of techniques an adversary may use to gain knowledge about the system and internal network. These techniques help adversaries observe the environment and orient themselves before deciding how to act. They also allow adversaries to explore what they can control and what's around their entry point in order to discover how it could benefit their current objective. Native operating system tools are often used toward this post-compromise information-gathering objective. Building an isolated PAW and network, supported by well-defined security policies and controlled data transfer processes, significantly reduces the ability of a threat actor to discover vulnerabilities or perform reconnaissance on systems and services. Isolation limits exposure to untrusted networks, while structured data flows ensure that only authorized and validated interactions occur. This approach not only minimizes the attack surface but also disrupts common tactics such as lateral movement and privilege escalation, making reconnaissance and exploitation substantially more difficult. ETSI ETSI TS 103 994-3 V1.1.1 (2026-01) 15 Annex A (informative): Bibliography • MITRE ATT&CK®: "Credential Access". • MITRE ATT&CK®: "Exfiltration". • MITRE ATT&CK®: "Lateral Movement". • MITRE ATT&CK®: "Discovery". • MITRE ATT&CK®: "Reconnaissance". • NCSP: "Principles for secure privileged access workstations (PAWs)". ETSI ETSI TS 103 994-3 V1.1.1 (2026-01) 16 Annex B (informative): Change history Date Version Information about changes November 2025 V0.0.1 First draft November 2025 V0.0.2 Minor editorials & Section 8 Completed November 2025 V0.0.3 Minor editorials - hanging text and references ETSI ETSI TS 103 994-3 V1.1.1 (2026-01) 17 History Version Date Status V1.1.1 January 2026 Publication |
dba25161077ab25d04f1eb028c9d59ca | 104 126 | 1 Scope | The present document contains the following material relating to takedown requests: • A statement of benefits for using standardized interfaces for takedown requests. • Suggestions around potential requirements (though the present document does not formally define requirements). • Use cases, examples and scenarios which are brought together into categories (the goal is that all scenarios in the same category can be handled in a similar way). • Potential approaches for each category i.e. ways to achieve the benefits for the scenarios identified (the approaches considered include creating new standards and creating Change Requests against existing standards. |
dba25161077ab25d04f1eb028c9d59ca | 104 126 | 2 References | |
dba25161077ab25d04f1eb028c9d59ca | 104 126 | 2.1 Normative references | Normative references are not applicable in the present document. |
dba25161077ab25d04f1eb028c9d59ca | 104 126 | 2.2 Informative references | References are either specific (identified by date of publication and/or edition number or version number) or non-specific. For specific references, only the cited version applies. For non-specific references, the latest version of the referenced document (including any amendments) applies. NOTE: While any hyperlinks included in this clause were valid at the time of publication, ETSI cannot guarantee their long-term validity. The following referenced documents may be useful in implementing an ETSI deliverable or add to the reader's understanding, but are not required for conformance to the present document. [i.1] ETSI TS 103 120: "Lawful Interception (LI); Interface for warrant information". |
dba25161077ab25d04f1eb028c9d59ca | 104 126 | 3 Definition of terms, symbols and abbreviations | |
dba25161077ab25d04f1eb028c9d59ca | 104 126 | 3.1 Terms | Void. |
dba25161077ab25d04f1eb028c9d59ca | 104 126 | 3.2 Symbols | Void. |
dba25161077ab25d04f1eb028c9d59ca | 104 126 | 3.3 Abbreviations | For the purposes of the present document, the following abbreviations apply: DNS Domain Name System IP Internet Protocol ETSI ETSI TR 104 126 V1.1.1 (2026-02) 6 |
dba25161077ab25d04f1eb028c9d59ca | 104 126 | 4 Core concepts |
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