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cs/0701160
Supporting Finite Element Analysis with a Relational Database Backend, Part II: Database Design and Access
cs.DB cs.CE
This is Part II of a three article series on using databases for Finite Element Analysis (FEA). It discusses (1) db design, (2) data loading, (3) typical use cases during grid building, (4) typical use cases during simulation (get and put), (5) typical use cases during analysis (also done in Part III) and some performance measures of these cases. It argues that using a database is simpler to implement than custom data schemas, has better performance because it can use data parallelism, and better supports FEA modularity and tool evolution because database schema evolution, data independence, and self-defining data.
cs/0701161
Thousands of DebitCredit Transactions-Per-Second: Easy and Inexpensive
cs.DB cs.PF
A $2k computer can execute about 8k transactions per second. This is 80x more than one of the largest US bank's 1970's traffic - it approximates the total US 1970's financial transaction volume. Very modest modern computers can easily solve yesterday's problems.
cs/0701162
A Measure of Transaction Processing 20 Years Later
cs.DB cs.PF
This provides a retrospective of the paper "A Measure of Transaction Processing" published in 1985. It shows that transaction processing peak performance and price-peformance have improved about 100,000x respectively and that sort/sequential performance has approximately doubled each year (so a million fold improvement) even though processor performance plateaued in 1995.
cs/0701163
Using Table Valued Functions in SQL Server 2005 To Implement a Spatial Data Library
cs.DB cs.CE
This article explains how to add spatial search functions (point-near-point and point in polygon) to Microsoft SQL Server 2005 using C# and table-valued functions. It is possible to use this library to add spatial search to your application without writing any special code. The library implements the public-domain C# Hierarchical Triangular Mesh (HTM) algorithms from Johns Hopkins University. That C# library is connected to SQL Server 2005 via a set of scalar-valued and table-valued functions. These functions act as a spatial index.
cs/0701164
Indexing the Sphere with the Hierarchical Triangular Mesh
cs.DB cs.DS
We describe a method to subdivide the surface of a sphere into spherical triangles of similar, but not identical, shapes and sizes. The Hierarchical Triangular Mesh (HTM) is a quad-tree that is particularly good at supporting searches at different resolutions, from arc seconds to hemispheres. The subdivision scheme is universal, providing the basis for addressing and for fast lookups. The HTM provides the basis for an efficient geospatial indexing scheme in relational databases where the data have an inherent location on either the celestial sphere or the Earth. The HTM index is superior to cartographical methods using coordinates with singularities at the poles. We also describe a way to specify surface regions that efficiently represent spherical query areas. This article presents the algorithms used to identify the HTM triangles covering such regions.
cs/0701165
Petascale Computational Systems
cs.DB cs.AR
Computational science is changing to be data intensive. Super-Computers must be balanced systems; not just CPU farms but also petascale IO and networking arrays. Anyone building CyberInfrastructure should allocate resources to support a balanced Tier-1 through Tier-3 design.
cs/0701166
Empirical Measurements of Disk Failure Rates and Error Rates
cs.DB cs.AR
The SATA advertised bit error rate of one error in 10 terabytes is frightening. We moved 2 PB through low-cost hardware and saw five disk read error events, several controller failures, and many system reboots caused by security patches. We conclude that SATA uncorrectable read errors are not yet a dominant system-fault source - they happen, but are rare compared to other problems. We also conclude that UER (uncorrectable error rate) is not the relevant metric for our needs. When an uncorrectable read error happens, there are typically several damaged storage blocks (and many uncorrectable read errors.) Also, some uncorrectable read errors may be masked by the operating system. The more meaningful metric for data architects is Mean Time To Data Loss (MTTDL.)
cs/0701167
Large-Scale Query and XMatch, Entering the Parallel Zone
cs.DB cs.CE
Current and future astronomical surveys are producing catalogs with millions and billions of objects. On-line access to such big datasets for data mining and cross-correlation is usually as highly desired as unfeasible. Providing these capabilities is becoming critical for the Virtual Observatory framework. In this paper we present various performance tests that show how using Relational Database Management Systems (RDBMS) and a Zoning algorithm to partition and parallelize the computation, we can facilitate large-scale query and cross-match.
cs/0701168
To BLOB or Not To BLOB: Large Object Storage in a Database or a Filesystem?
cs.DB
Application designers often face the question of whether to store large objects in a filesystem or in a database. Often this decision is made for application design simplicity. Sometimes, performance measurements are also used. This paper looks at the question of fragmentation - one of the operational issues that can affect the performance and/or manageability of the system as deployed long term. As expected from the common wisdom, objects smaller than 256KB are best stored in a database while objects larger than 1M are best stored in the filesystem. Between 256KB and 1MB, the read:write ratio and rate of object overwrite or replacement are important factors. We used the notion of "storage age" or number of object overwrites as way of normalizing wall clock time. Storage age allows our results or similar such results to be applied across a number of read:write ratios and object replacement rates.
cs/0701169
A Framework for Designing MIMO systems with Decision Feedback Equalization or Tomlinson-Harashima Precoding
cs.IT math.IT
We consider joint transceiver design for general Multiple-Input Multiple-Output communication systems that implement interference (pre-)subtraction, such as those based on Decision Feedback Equalization (DFE) or Tomlinson-Harashima precoding (THP). We develop a unified framework for joint transceiver design by considering design criteria that are expressed as functions of the Mean Square Error (MSE) of the individual data streams. By deriving two inequalities that involve the logarithms of the individual MSEs, we obtain optimal designs for two classes of communication objectives, namely those that are Schur-convex and Schur-concave functions of these logarithms. For Schur-convex objectives, the optimal design results in data streams with equal MSEs. This design simultaneously minimizes the total MSE and maximizes the mutual information for the DFE-based model. For Schur-concave objectives, the optimal DFE design results in linear equalization and the optimal THP design results in linear precoding. The proposed framework embraces a wide range of design objectives and can be regarded as a counterpart of the existing framework of linear transceiver design.
cs/0701170
Life Under Your Feet: An End-to-End Soil Ecology Sensor Network, Database, Web Server, and Analysis Service
cs.DB cs.CE
Wireless sensor networks can revolutionize soil ecology by providing measurements at temporal and spatial granularities previously impossible. This paper presents a soil monitoring system we developed and deployed at an urban forest in Baltimore as a first step towards realizing this vision. Motes in this network measure and save soil moisture and temperature in situ every minute. Raw measurements are periodically retrieved by a sensor gateway and stored in a central database where calibrated versions are derived and stored. The measurement database is published through Web Services interfaces. In addition, analysis tools let scientists analyze current and historical data and help manage the sensor network. The article describes the system design, what we learned from the deployment, and initial results obtained from the sensors. The system measures soil factors with unprecedented temporal precision. However, the deployment required device-level programming, sensor calibration across space and time, and cross-referencing measurements with external sources. The database, web server, and data analysis design required considerable innovation and expertise. So, the ratio of computer-scientists to ecologists was 3:1. Before sensor networks can fulfill their potential as instruments that can be easily deployed by scientists, these technical problems must be addressed so that the ratio is one nerd per ten ecologists.
cs/0701171
The Zones Algorithm for Finding Points-Near-a-Point or Cross-Matching Spatial Datasets
cs.DB cs.DS
Zones index an N-dimensional Euclidian or metric space to efficiently support points-near-a-point queries either within a dataset or between two datasets. The approach uses relational algebra and the B-Tree mechanism found in almost all relational database systems. Hence, the Zones Algorithm gives a portable-relational implementation of points-near-point, spatial cross-match, and self-match queries. This article corrects some mistakes in an earlier article we wrote on the Zones Algorithm and describes some algorithmic improvements. The Appendix includes an implementation of point-near-point, self-match, and cross-match using the USGS city and stream gauge database.
cs/0701172
Cross-Matching Multiple Spatial Observations and Dealing with Missing Data
cs.DB cs.CE
Cross-match spatially clusters and organizes several astronomical point-source measurements from one or more surveys. Ideally, each object would be found in each survey. Unfortunately, the observation conditions and the objects themselves change continually. Even some stationary objects are missing in some observations; sometimes objects have a variable light flux and sometimes the seeing is worse. In most cases we are faced with a substantial number of differences in object detections between surveys and between observations taken at different times within the same survey or instrument. Dealing with such missing observations is a difficult problem. The first step is to classify misses as ephemeral - when the object moved or simply disappeared, masked - when noise hid or corrupted the object observation, or edge - when the object was near the edge of the observational field. This classification and a spatial library to represent and manipulate observational footprints help construct a Match table recording both hits and misses. Transitive closure clusters friends-of-friends into object bundles. The bundle summary statistics are recorded in a Bundle table. This design is an evolution of the Sloan Digital Sky Survey cross-match design that compared overlapping observations taken at different times. Cross-Matching Multiple Spatial Observations and Dealing with Missing Data.
cs/0701173
SkyServer Traffic Report - The First Five Years
cs.DB cs.CE
The SkyServer is an Internet portal to the Sloan Digital Sky Survey Catalog Archive Server. From 2001 to 2006, there were a million visitors in 3 million sessions generating 170 million Web hits, 16 million ad-hoc SQL queries, and 62 million page views. The site currently averages 35 thousand visitors and 400 thousand sessions per month. The Web and SQL logs are public. We analyzed traffic and sessions by duration, usage pattern, data product, and client type (mortal or bot) over time. The analysis shows (1) the site's popularity, (2) the educational website that delivered nearly fifty thousand hours of interactive instruction, (3) the relative use of interactive, programmatic, and batch-local access, (4) the success of offering ad-hoc SQL, personal database, and batch job access to scientists as part of the data publication, (5) the continuing interest in "old" datasets, (6) the usage of SQL constructs, and (7) a novel approach of using the corpus of correct SQL queries to suggest similar but correct statements when a user presents an incorrect SQL statement.
cs/0701174
A Prototype for Educational Planning Using Course Constraints to Simulate Student Populations
cs.AI cs.CY cs.DS cs.SC
Distance learning universities usually afford their students the flexibility to advance their studies at their own pace. This can lead to a considerable fluctuation of student populations within a program's courses, possibly affecting the academic viability of a program as well as the related required resources. Providing a method that estimates this population could be of substantial help to university management and academic personnel. We describe how to use course precedence constraints to calculate alternative tuition paths and then use Markov models to estimate future populations. In doing so, we identify key issues of a large scale potential deployment.
cs/0701178
Distributed Detection in Sensor Networks with Limited Range Sensors
cs.IT math.IT
We consider a multi-object detection problem over a sensor network (SNET) with limited range sensors. This problem complements the widely considered decentralized detection problem where all sensors observe the same object. While the necessity for global collaboration is clear in the decentralized detection problem, the benefits of collaboration with limited range sensors is unclear and has not been widely explored. In this paper we develop a distributed detection approach based on recent development of the false discovery rate (FDR). We first extend the FDR procedure and develop a transformation that exploits complete or partial knowledge of either the observed distributions at each sensor or the ensemble (mixture) distribution across all sensors. We then show that this transformation applies to multi-dimensional observations, thus extending FDR to multi-dimensional settings. We also extend FDR theory to cases where distributions under both null and positive hypotheses are uncertain. We then propose a robust distributed algorithm to perform detection. We further demonstrate scalability to large SNETs by showing that the upper bound on the communication complexity scales linearly with the number of sensors that are in the vicinity of objects and is independent of the total number of sensors. Finally, we deal with situations where the sensing model may be uncertain and establish robustness of our techniques to such uncertainties.
cs/0701180
Ontology from Local Hierarchical Structure in Text
cs.IR
We study the notion of hierarchy in the context of visualizing textual data and navigating text collections. A formal framework for ``hierarchy'' is given by an ultrametric topology. This provides us with a theoretical foundation for concept hierarchy creation. A major objective is {\em scalable} annotation or labeling of concept maps. Serendipitously we pursue other objectives such as deriving common word pair (and triplet) phrases, i.e., word 2- and 3-grams. We evaluate our approach using (i) a collection of texts, (ii) a single text subdivided into successive parts (for which we provide an interactive demonstrator), and (iii) a text subdivided at the sentence or line level. While detailing a generic framework, a distinguishing feature of our work is that we focus on {\em locality} of hierarchic structure in order to extract semantic information.
cs/0701181
A Note on Local Ultrametricity in Text
cs.CL
High dimensional, sparsely populated data spaces have been characterized in terms of ultrametric topology. This implies that there are natural, not necessarily unique, tree or hierarchy structures defined by the ultrametric topology. In this note we study the extent of local ultrametric topology in texts, with the aim of finding unique ``fingerprints'' for a text or corpus, discriminating between texts from different domains, and opening up the possibility of exploiting hierarchical structures in the data. We use coherent and meaningful collections of over 1000 texts, comprising over 1.3 million words.
cs/0701182
Supplement to: Code Spectrum and Reliability Function: Binary Symmetric Channel
cs.IT math.IT
A much simpler proof of Theorem 1 from M.Burnashev "Code spectrum and reliability function: Binary symmetric channel" is presented.
cs/0701184
Structure and Problem Hardness: Goal Asymmetry and DPLL Proofs in<br> SAT-Based Planning
cs.AI
In Verification and in (optimal) AI Planning, a successful method is to formulate the application as boolean satisfiability (SAT), and solve it with state-of-the-art DPLL-based procedures. There is a lack of understanding of why this works so well. Focussing on the Planning context, we identify a form of problem structure concerned with the symmetrical or asymmetrical nature of the cost of achieving the individual planning goals. We quantify this sort of structure with a simple numeric parameter called AsymRatio, ranging between 0 and 1. We run experiments in 10 benchmark domains from the International Planning Competitions since 2000; we show that AsymRatio is a good indicator of SAT solver performance in 8 of these domains. We then examine carefully crafted synthetic planning domains that allow control of the amount of structure, and that are clean enough for a rigorous analysis of the combinatorial search space. The domains are parameterized by size, and by the amount of structure. The CNFs we examine are unsatisfiable, encoding one planning step less than the length of the optimal plan. We prove upper and lower bounds on the size of the best possible DPLL refutations, under different settings of the amount of structure, as a function of size. We also identify the best possible sets of branching variables (backdoors). With minimum AsymRatio, we prove exponential lower bounds, and identify minimal backdoors of size linear in the number of variables. With maximum AsymRatio, we identify logarithmic DPLL refutations (and backdoors), showing a doubly exponential gap between the two structural extreme cases. The reasons for this behavior -- the proof arguments -- illuminate the prototypical patterns of structure causing the empirical behavior observed in the competition benchmarks.
cs/0701194
Menzerath-Altmann Law for Syntactic Structures in Ukrainian
cs.CL
In the paper, the definition of clause suitable for an automated processing of a Ukrainian text is proposed. The Menzerath-Altmann law is verified on the sentence level and the parameters for the dependences of the clause length counted in words and syllables on the sentence length counted in clauses are calculated for "Perekhresni Stezhky" ("The Cross-Paths"), a novel by Ivan Franko.
cs/0701196
One-bit Distributed Sensing and Coding for Field Estimation in Sensor Networks
cs.IT math.IT
This paper formulates and studies a general distributed field reconstruction problem using a dense network of noisy one-bit randomized scalar quantizers in the presence of additive observation noise of unknown distribution. A constructive quantization, coding, and field reconstruction scheme is developed and an upper-bound to the associated mean squared error (MSE) at any point and any snapshot is derived in terms of the local spatio-temporal smoothness properties of the underlying field. It is shown that when the noise, sensor placement pattern, and the sensor schedule satisfy certain weak technical requirements, it is possible to drive the MSE to zero with increasing sensor density at points of field continuity while ensuring that the per-sensor bitrate and sensing-related network overhead rate simultaneously go to zero. The proposed scheme achieves the order-optimal MSE versus sensor density scaling behavior for the class of spatially constant spatio-temporal fields.
cs/0701197
On Delayed Sequential Coding of Correlated Sources
cs.IT math.IT
Motivated by video coding applications, the problem of sequential coding of correlated sources with encoding and/or decoding frame-delays is studied. The fundamental tradeoffs between individual frame rates, individual frame distortions, and encoding/decoding frame-delays are derived in terms of a single-letter information-theoretic characterization of the rate-distortion region for general inter-frame source correlations and certain types of potentially frame specific and coupled single-letter fidelity criteria. The sum-rate-distortion region is characterized in terms of generalized directed information measures highlighting their role in delayed sequential source coding problems. For video sources which are spatially stationary memoryless and temporally Gauss-Markov, MSE frame distortions, and a sum-rate constraint, our results expose the optimality of idealized differential predictive coding among all causal sequential coders, when the encoder uses a positive rate to describe each frame. Somewhat surprisingly, causal sequential encoding with one-frame-delayed noncausal sequential decoding can exactly match the sum-rate-MSE performance of joint coding for all nontrivial MSE-tuples satisfying certain positive semi-definiteness conditions. Thus, even a single frame-delay holds potential for yielding significant performance improvements. Generalizations to higher order Markov sources are also presented and discussed. A rate-distortion performance equivalence between, causal sequential encoding with delayed noncausal sequential decoding, and, delayed noncausal sequential encoding with causal sequential decoding, is also established.
cs/0702007
Power Optimal Scheduling for Guaranteed Throughput in Multi-access Fading Channels
cs.IT math.IT
A power optimal scheduling algorithm that guarantees desired throughput and bounded delay to each user is developed for fading multi-access multi-band systems. The optimization is over the joint space of all rate allocation and coding strategies. The proposed scheduling assigns rates on each band based only on the current system state, and subsequently uses optimal multi-user signaling to achieve these rates. The scheduling is computationally simple, and hence scalable. Due to uplink-downlink duality, all the results extend in straightforward fashion to the broadcast channels.
cs/0702008
MMSE Optimal Algebraic Space-Time Codes
cs.IT math.IT
Design of Space-Time Block Codes (STBCs) for Maximum Likelihood (ML) reception has been predominantly the main focus of researchers. However, the ML decoding complexity of STBCs becomes prohibitive large as the number of transmit and receive antennas increase. Hence it is natural to resort to a suboptimal reception technique like linear Minimum Mean Squared Error (MMSE) receiver. Barbarossa et al and Liu et al have independently derived necessary and sufficient conditions for a full rate linear STBC to be MMSE optimal, i.e achieve least Symbol Error Rate (SER). Motivated by this problem, certain existing high rate STBC constructions from crossed product algebras are identified to be MMSE optimal. Also, it is shown that a certain class of codes from cyclic division algebras which are special cases of crossed product algebras are MMSE optimal. Hence, these STBCs achieve least SER when MMSE reception is employed and are fully diverse when ML reception is employed.
cs/0702009
On Evaluating the Rate-Distortion Function of Sources with Feed-Forward and the Capacity of Channels with Feedback
cs.IT math.IT
We study the problem of computing the rate-distortion function for sources with feed-forward and the capacity for channels with feedback. The formulas (involving directed information) for the optimal rate-distortion function with feed-forward and channel capacity with feedback are multi-letter expressions and cannot be computed easily in general. In this work, we derive conditions under which these can be computed for a large class of sources/channels with memory and distortion/cost measures. Illustrative examples are also provided.
cs/0702011
Dealing With Logical Omniscience: Expressiveness and Pragmatics
cs.LO cs.AI
We examine four approaches for dealing with the logical omniscience problem and their potential applicability: the syntactic approach, awareness, algorithmic knowledge, and impossible possible worlds. Although in some settings these approaches are equi-expressive and can capture all epistemic states, in other settings of interest (especially with probability in the picture), we show that they are not equi-expressive. We then consider the pragmatics of dealing with logical omniscience-- how to choose an approach and construct an appropriate model.
cs/0702012
Plagiarism Detection in arXiv
cs.DB cs.DL cs.IR
We describe a large-scale application of methods for finding plagiarism in research document collections. The methods are applied to a collection of 284,834 documents collected by arXiv.org over a 14 year period, covering a few different research disciplines. The methodology efficiently detects a variety of problematic author behaviors, and heuristics are developed to reduce the number of false positives. The methods are also efficient enough to implement as a real-time submission screen for a collection many times larger.
cs/0702014
Probabilistic Analysis of Linear Programming Decoding
cs.IT cs.DM math.IT
We initiate the probabilistic analysis of linear programming (LP) decoding of low-density parity-check (LDPC) codes. Specifically, we show that for a random LDPC code ensemble, the linear programming decoder of Feldman et al. succeeds in correcting a constant fraction of errors with high probability. The fraction of correctable errors guaranteed by our analysis surpasses previous non-asymptotic results for LDPC codes, and in particular exceeds the best previous finite-length result on LP decoding by a factor greater than ten. This improvement stems in part from our analysis of probabilistic bit-flipping channels, as opposed to adversarial channels. At the core of our analysis is a novel combinatorial characterization of LP decoding success, based on the notion of a generalized matching. An interesting by-product of our analysis is to establish the existence of ``probabilistic expansion'' in random bipartite graphs, in which one requires only that almost every (as opposed to every) set of a certain size expands, for sets much larger than in the classical worst-case setting.
cs/0702015
Network Coding for Distributed Storage Systems
cs.IT cs.NI math.IT
Peer-to-peer distributed storage systems provide reliable access to data through redundancy spread over nodes across the Internet. A key goal is to minimize the amount of bandwidth used to maintain that redundancy. Storing a file using an erasure code, in fragments spread across nodes, promises to require less redundancy and hence less maintenance bandwidth than simple replication to provide the same level of reliability. However, since fragments must be periodically replaced as nodes fail, a key question is how to generate a new fragment in a distributed way while transferring as little data as possible across the network. In this paper, we introduce a general technique to analyze storage architectures that combine any form of coding and replication, as well as presenting two new schemes for maintaining redundancy using erasure codes. First, we show how to optimally generate MDS fragments directly from existing fragments in the system. Second, we introduce a new scheme called Regenerating Codes which use slightly larger fragments than MDS but have lower overall bandwidth use. We also show through simulation that in realistic environments, Regenerating Codes can reduce maintenance bandwidth use by 25 percent or more compared with the best previous design--a hybrid of replication and erasure codes--while simplifying system architecture.
cs/0702017
Comment on Improved Analysis of List Decoding and Its Application to Convolutional Codes and Turbo Codes
cs.IT math.IT
In a recent paper [1] an improved analysis concerning the analysis of List Decoding was presented. The event that the correct codeword is excluded from the list is central. For the additive white Gaussian noise (AWGN) channel an important quantity is the in [1] called effective Euclidean distance. This was earlier considered in [2] under the name Vector Euclidean Distance, where also a simple mathematical expression for this quantity was easily derived for any list size. In [1], a geometrical analysis gives this when the list size is 1, 2 or 3.
cs/0702018
Estimation of the Rate-Distortion Function
cs.IT math.IT math.ST stat.TH
Motivated by questions in lossy data compression and by theoretical considerations, we examine the problem of estimating the rate-distortion function of an unknown (not necessarily discrete-valued) source from empirical data. Our focus is the behavior of the so-called "plug-in" estimator, which is simply the rate-distortion function of the empirical distribution of the observed data. Sufficient conditions are given for its consistency, and examples are provided to demonstrate that in certain cases it fails to converge to the true rate-distortion function. The analysis of its performance is complicated by the fact that the rate-distortion function is not continuous in the source distribution; the underlying mathematical problem is closely related to the classical problem of establishing the consistency of maximum likelihood estimators. General consistency results are given for the plug-in estimator applied to a broad class of sources, including all stationary and ergodic ones. A more general class of estimation problems is also considered, arising in the context of lossy data compression when the allowed class of coding distributions is restricted; analogous results are developed for the plug-in estimator in that case. Finally, consistency theorems are formulated for modified (e.g., penalized) versions of the plug-in, and for estimating the optimal reproduction distribution.
cs/0702020
Construction of Minimal Tail-Biting Trellises for Codes over Finite Abelian Groups
cs.IT math.IT
A definition of atomic codeword for a group code is presented. Some properties of atomic codewords of group codes are investigated. Using these properties, it is shown that every minimal tail-biting trellis for a group code over a finite abelian group can be constructed from its characteristic generators, which extends the work of Koetter and Vardy who treated the case of a linear code over a field. We also present an efficient algorithm for constructing the minimal tail-biting trellis of a group code over a finite abelian group, given a generator matrix.
cs/0702023
High-rate, Multi-Symbol-Decodable STBCs from Clifford Algebras
cs.IT math.IT
It is well known that Space-Time Block Codes (STBCs) obtained from Orthogonal Designs (ODs) are single-symbol-decodable (SSD) and from Quasi-Orthogonal Designs (QODs) are double-symbol decodable. However, there are SSD codes that are not obtainable from ODs and DSD codes that are not obtainable from QODs. In this paper a method of constructing $g$-symbol decodable ($g$-SD) STBCs using representations of Clifford algebras are presented which when specialized to $g=1,2$ gives SSD and DSD codes respectively. For the number of transmit antennas $2^a$ the rate (in complex symbols per channel use) of the $g$-SD codes presented in this paper is $\frac{a+1-g}{2^{a-g}}$. The maximum rate of the DSD STBCs from QODs reported in the literature is $\frac{a}{2^{a-1}}$ which is smaller than the rate $\frac{a-1}{2^{a-2}}$ of the DSD codes of this paper, for $2^a$ transmit antennas. In particular, the reported DSD codes for 8 and 16 transmit antennas offer rates 1 and 3/4 respectively whereas the known STBCs from QODs offer only 3/4 and 1/2 respectively. The construction of this paper is applicable for any number of transmit antennas.
cs/0702024
Searching for low weight pseudo-codewords
cs.IT math.IT
Belief Propagation (BP) and Linear Programming (LP) decodings of Low Density Parity Check (LDPC) codes are discussed. We summarize results of instanton/pseudo-codeword approach developed for analysis of the error-floor domain of the codes. Instantons are special, code and decoding specific, configurations of the channel noise contributing most to the Frame-Error-Rate (FER). Instantons are decoded into pseudo-codewords. Instanton/pseudo-codeword with the lowest weight describes the largest Signal-to-Noise-Ratio (SNR) asymptotic of FER, while the whole spectra of the low weight instantons is descriptive of the FER vs SNR profile in the extended error-floor domain. First, we describe a general optimization method that allows to find the instantons for any coding/decoding. Second, we introduce LP-specific pseudo-codeword search algorithm that allows efficient calculations of the pseudo-codeword spectra. Finally, we discuss results of combined BP/LP error-floor exploration experiments for two model codes.
cs/0702025
Algebraic Signal Processing Theory: Cooley-Tukey Type Algorithms for DCTs and DSTs
cs.IT cs.DS math.IT
This paper presents a systematic methodology based on the algebraic theory of signal processing to classify and derive fast algorithms for linear transforms. Instead of manipulating the entries of transform matrices, our approach derives the algorithms by stepwise decomposition of the associated signal models, or polynomial algebras. This decomposition is based on two generic methods or algebraic principles that generalize the well-known Cooley-Tukey FFT and make the algorithms' derivations concise and transparent. Application to the 16 discrete cosine and sine transforms yields a large class of fast algorithms, many of which have not been found before.
cs/0702028
Uniform and Partially Uniform Redistribution Rules
cs.AI
This short paper introduces two new fusion rules for combining quantitative basic belief assignments. These rules although very simple have not been proposed in literature so far and could serve as useful alternatives because of their low computation cost with respect to the recent advanced Proportional Conflict Redistribution rules developed in the DSmT framework.
cs/0702030
Optimizing the SINR operating point of spatial networks
cs.IT math.IT
This paper addresses the following question, which is of interest in the design and deployment of a multiuser decentralized network. Given a total system bandwidth of W Hz and a fixed data rate constraint of R bps for each transmission, how many frequency slots N of size W/N should the band be partitioned into to maximize the number of simultaneous transmissions in the network? In an interference-limited ad-hoc network, dividing the available spectrum results in two competing effects: on the positive side, it reduces the number of users on each band and therefore decreases the interference level which leads to an increased SINR, while on the negative side the SINR requirement for each transmission is increased because the same information rate must be achieved over a smaller bandwidth. Exploring this tradeoff between bandwidth and SINR and determining the optimum value of N in terms of the system parameters is the focus of the paper. Using stochastic geometry, we analytically derive the optimal SINR threshold (which directly corresponds to the optimal spectral efficiency) on this tradeoff curve and show that it is a function of only the path loss exponent. Furthermore, the optimal SINR point lies between the low-SINR (power-limited) and high-SINR (bandwidth-limited) regimes. In order to operate at this optimal point, the number of frequency bands (i.e., the reuse factor) should be increased until the threshold SINR, which is an increasing function of the reuse factor, is equal to the optimal value.
cs/0702031
Quantized vs. Analog Feedback for the MIMO Downlink: A Comparison between Zero-Forcing Based Achievable Rates
cs.IT math.IT
We consider a MIMO fading broadcast channel and compare the achievable ergodic rates when the channel state information at the transmitter is provided by analog noisy feedback or by quantized (digital) feedback. The superiority of digital feedback is shown, with perfect or imperfect CSIR, whenever the number of feedback channel uses per channel coefficient is larger than 1. Also, we show that by proper design of the digital feedback link, errors in the feedback have a minor effect even by using very simple uncoded modulation. Finally, we show that analog feedback achieves a fraction 1 - 2F of the optimal multiplexing gain even in the presence of a feedback delay, when the fading belongs to the class of Doppler processes with normalized maximum Doppler frequency shift 0 <= F <= 1/2.
cs/0702033
Bounds on ordered codes and orthogonal arrays
cs.IT math.CO math.IT
We derive new estimates of the size of codes and orthogonal arrays in the ordered Hamming space (the Niederreiter-Rosenbloom-Tsfasman space). We also show that the eigenvalues of the ordered Hamming scheme, the association scheme that describes the combinatorics of the space, are given by the multivariable Krawtchouk polynomials, and establish some of their properties.
cs/0702035
New Models for the Correlation in Sensor Data
cs.IT math.IT
In this paper, we propose two new models of spatial correlations in sensor data in a data-gathering sensor network. A particular property of these models is that if a sensor node knows in \textit{how many} bits it needs to transmit its data, then it also knows \textit{which} bits of its data it needs to transmit.
cs/0702037
Evolutionary Approaches to Minimizing Network Coding Resources
cs.NI cs.IT math.IT
We wish to minimize the resources used for network coding while achieving the desired throughput in a multicast scenario. We employ evolutionary approaches, based on a genetic algorithm, that avoid the computational complexity that makes the problem NP-hard. Our experiments show great improvements over the sub-optimal solutions of prior methods. Our new algorithms improve over our previously proposed algorithm in three ways. First, whereas the previous algorithm can be applied only to acyclic networks, our new method works also with networks with cycles. Second, we enrich the set of components used in the genetic algorithm, which improves the performance. Third, we develop a novel distributed framework. Combining distributed random network coding with our distributed optimization yields a network coding protocol where the resources used for coding are optimized in the setup phase by running our evolutionary algorithm at each node of the network. We demonstrate the effectiveness of our approach by carrying out simulations on a number of different sets of network topologies.
cs/0702038
Genetic Representations for Evolutionary Minimization of Network Coding Resources
cs.NE cs.NI
We demonstrate how a genetic algorithm solves the problem of minimizing the resources used for network coding, subject to a throughput constraint, in a multicast scenario. A genetic algorithm avoids the computational complexity that makes the problem NP-hard and, for our experiments, greatly improves on sub-optimal solutions of established methods. We compare two different genotype encodings, which tradeoff search space size with fitness landscape, as well as the associated genetic operators. Our finding favors a smaller encoding despite its fewer intermediate solutions and demonstrates the impact of the modularity enforced by genetic operators on the performance of the algorithm.
cs/0702044
Transmission Capacity of Ad Hoc Networks with Spatial Diversity
cs.IT math.IT
This paper derives the outage probability and transmission capacity of ad hoc wireless networks with nodes employing multiple antenna diversity techniques, for a general class of signal distributions. This analysis allows system performance to be quantified for fading or non-fading environments. The transmission capacity is given for interference-limited uniformly random networks on the entire plane with path loss exponent $\alpha>2$ in which nodes use: (1) static beamforming through $M$ sectorized antennas, for which the increase in transmission capacity is shown to be $\Theta(M^2)$ if the antennas are without sidelobes, but less in the event of a nonzero sidelobe level; (2) dynamic eigen-beamforming (maximal ratio transmission/combining), in which the increase is shown to be $\Theta(M^{\frac{2}{\alpha}})$; (3) various transmit antenna selection and receive antenna selection combining schemes, which give appreciable but rapidly diminishing gains; and (4) orthogonal space-time block coding, for which there is only a small gain due to channel hardening, equivalent to Nakagami-$m$ fading for increasing $m$. It is concluded that in ad hoc networks, static and dynamic beamforming perform best, selection combining performs well but with rapidly diminishing returns with added antennas, and that space-time block coding offers only marginal gains.
cs/0702045
Gaussian Interference Channel Capacity to Within One Bit
cs.IT math.IT
The capacity of the two-user Gaussian interference channel has been open for thirty years. The understanding on this problem has been limited. The best known achievable region is due to Han-Kobayashi but its characterization is very complicated. It is also not known how tight the existing outer bounds are. In this work, we show that the existing outer bounds can in fact be arbitrarily loose in some parameter ranges, and by deriving new outer bounds, we show that a simplified Han-Kobayashi type scheme can achieve to within a single bit the capacity for all values of the channel parameters. We also show that the scheme is asymptotically optimal at certain high SNR regimes. Using our results, we provide a natural generalization of the point-to-point classical notion of degrees of freedom to interference-limited scenarios.
cs/0702050
Permutation Decoding and the Stopping Redundancy Hierarchy of Linear Block Codes
cs.IT math.IT
We investigate the stopping redundancy hierarchy of linear block codes and its connection to permutation decoding techniques. An element in the ordered list of stopping redundancy values represents the smallest number of possibly linearly dependent rows in any parity-check matrix of a code that avoids stopping sets of a given size. Redundant parity-check equations can be shown to have a similar effect on decoding performance as permuting the coordinates of the received codeword according to a selected set of automorphisms of the code. Based on this finding we develop new decoding strategies for data transmission over the binary erasure channel that combine iterative message passing and permutation decoding in order to avoid errors confined to stopping sets. We also introduce the notion of s-SAD sets, containing the smallest number of automorphisms of a code with the property that they move any set of not more than s erasures into positions that do not correspond to stopping sets within a judiciously chosen parity-check matrix.
cs/0702051
The Gaussian multiple access wire-tap channel: wireless secrecy and cooperative jamming
cs.IT cs.CR math.IT
We consider the General Gaussian Multiple Access Wire-Tap Channel (GGMAC-WT). In this scenario, multiple users communicate with an intended receiver in the presence of an intelligent and informed eavesdropper. We define two suitable secrecy measures, termed individual and collective, to reflect the confidence in the system for this multi-access environment. We determine achievable rates such that secrecy to some pre-determined degree can be maintained, using Gaussian codebooks. We also find outer bounds for the case when the eavesdropper receives a degraded version of the intended receiver's signal. In the degraded case, Gaussian codewords are shown to achieve the sum capacity for collective constraints. In addition, a TDMA scheme is shown to also achieve sum capacity for both sets of constraints. Numerical results showing the new rate region are presented and compared with the capacity region of the Gaussian Multiple-Access Channel (GMAC) with no secrecy constraints. We then find the secrecy sum-rate maximizing power allocations for the transmitters, and show that a cooperative jamming scheme can be used to increase achievable rates in this scenario.
cs/0702052
On Random Network Coding for Multicast
cs.IT math.IT
Random linear network coding is a particularly decentralized approach to the multicast problem. Use of random network codes introduces a non-zero probability however that some sinks will not be able to successfully decode the required sources. One of the main theoretical motivations for random network codes stems from the lower bound on the probability of successful decoding reported by Ho et. al. (2003). This result demonstrates that all sinks in a linearly solvable network can successfully decode all sources provided that the random code field size is large enough. This paper develops a new bound on the probability of successful decoding.
cs/0702055
On the possibility of making the complete computer model of a human brain
cs.NE
The development of the algorithm of a neural network building by the corresponding parts of a DNA code is discussed.
cs/0702059
Redundancy-Related Bounds on Generalized Huffman Codes
cs.IT math.IT
This paper presents new lower and upper bounds for the compression rate of binary prefix codes optimized over memoryless sources according to various nonlinear codeword length objectives. Like the most well-known redundancy bounds for minimum average redundancy coding - Huffman coding - these are in terms of a form of entropy and/or the probability of an input symbol, often the most probable one. The bounds here, some of which are tight, improve on known bounds of the form L in [H,H+1), where H is some form of entropy in bits (or, in the case of redundancy objectives, 0) and L is the length objective, also in bits. The objectives explored here include exponential-average length, maximum pointwise redundancy, and exponential-average pointwise redundancy (also called dth exponential redundancy). The first of these relates to various problems involving queueing, uncertainty, and lossless communications; the second relates to problems involving Shannon coding and universal modeling. For these two objectives we also explore the related problem of the necessary and sufficient conditions for the shortest codeword of a code being a specific length.
cs/0702063
Entropy vectors and network codes
cs.IT cs.NI math.IT
We consider a network multicast example that relates the solvability of the multicast problem with the existence of an entropy function. As a result, we provide an alternative approach to the proving of the insufficiency of linear (and abelian) network codes and demonstrate the utility of non-Shannon inequalities to tighten outer bounds on network coding capacity regions.
cs/0702064
Group characterizable entropy functions
cs.IT math.IT
This paper studies properties of entropy functions that are induced by groups and subgroups. We showed that many information theoretic properties of those group induced entropy functions also have corresponding group theoretic interpretations. Then we propose an extension method to find outer bound for these group induced entropy functions.
cs/0702067
The Haar Wavelet Transform of a Dendrogram: Additional Notes
cs.IR
We consider the wavelet transform of a finite, rooted, node-ranked, $p$-way tree, focusing on the case of binary ($p = 2$) trees. We study a Haar wavelet transform on this tree. Wavelet transforms allow for multiresolution analysis through translation and dilation of a wavelet function. We explore how this works in our tree context.
cs/0702068
Distributed Decision Through Self-Synchronizing Sensor Networks in the Presence of Propagation Delays and Nonreciprocal Channels
cs.IT cs.MA math.IT
In this paper we propose and analyze a distributed algorithm for achieving globally optimal decisions, either estimation or detection, through a self-synchronization mechanism among linearly coupled integrators initialized with local measurements. We model the interaction among the nodes as a directed graph with weights dependent on the radio interface and we pose special attention to the effect of the propagation delays occurring in the exchange of data among sensors, as a function of the network geometry. We derive necessary and sufficient conditions for the proposed system to reach a consensus on globally optimal decision statistics. One of the major results proved in this work is that a consensus is achieved for any bounded delay condition if and only if the directed graph is quasi-strongly connected. We also provide a closed form expression for the global consensus, showing that the effect of delays is, in general, to introduce a bias in the final decision. The closed form expression is also useful to modify the consensus mechanism in order to get rid of the bias with minimum extra complexity.
cs/0702070
A Practical Approach to Lossy Joint Source-Channel Coding
cs.IT math.IT
This work is devoted to practical joint source channel coding. Although the proposed approach has more general scope, for the sake of clarity we focus on a specific application example, namely, the transmission of digital images over noisy binary-input output-symmetric channels. The basic building blocks of most state-of the art source coders are: 1) a linear transformation; 2) scalar quantization of the transform coefficients; 3) probability modeling of the sequence of quantization indices; 4) an entropy coding stage. We identify the weakness of the conventional separated source-channel coding approach in the catastrophic behavior of the entropy coding stage. Hence, we replace this stage with linear coding, that maps directly the sequence of redundant quantizer output symbols into a channel codeword. We show that this approach does not entail any loss of optimality in the asymptotic regime of large block length. However, in the practical regime of finite block length and low decoding complexity our approach yields very significant improvements. Furthermore, our scheme allows to retain the transform, quantization and probability modeling of current state-of the art source coders, that are carefully matched to the features of specific classes of sources. In our working example, we make use of ``bit-planes'' and ``contexts'' model defined by the JPEG2000 standard and we re-interpret the underlying probability model as a sequence of conditionally Markov sources. The Markov structure allows to derive a simple successive coding and decoding scheme, where the latter is based on iterative Belief Propagation. We provide a construction example of the proposed scheme based on punctured Turbo Codes and we demonstrate the gain over a conventional separated scheme by running extensive numerical experiments on test images.
cs/0702071
What is needed to exploit knowledge of primary transmissions?
cs.IT math.IT
Recently, Tarokh and others have raised the possibility that a cognitive radio might know the interference signal being transmitted by a strong primary user in a non-causal way, and use this knowledge to increase its data rates. However, there is a subtle difference between knowing the signal transmitted by the primary and the actual interference at our receiver since there is a wireless channel between these two points. We show that even an unknown phase results in a substantial decrease in the data rates that can be achieved, and thus there is a need to feedback interference channel estimates to the cognitive transmitter. We then consider the case of fading channels. We derive an upper bound on the rate for given outage error probability for faded dirt. We give a scheme that uses appropriate "training" to obtain such estimates and quantify this scheme's required overhead as a function of the relevant coherence time and interference power.
cs/0702072
Logic Programming with Satisfiability
cs.PL cs.AI
This paper presents a Prolog interface to the MiniSat satisfiability solver. Logic program- ming with satisfiability combines the strengths of the two paradigms: logic programming for encoding search problems into satisfiability on the one hand and efficient SAT solving on the other. This synergy between these two exposes a programming paradigm which we propose here as a logic programming pearl. To illustrate logic programming with SAT solving we give an example Prolog program which solves instances of Partial MAXSAT.
cs/0702073
Tradeoff between decoding complexity and rate for codes on graphs
cs.IT cs.CC math.IT
We consider transmission over a general memoryless channel, with bounded decoding complexity per bit under message passing decoding. We show that the achievable rate is bounded below capacity if there is a finite success in the decoding in a specified number of operations per bit at the decoder for some codes on graphs. These codes include LDPC and LDGM codes. Good performance with low decoding complexity suggests strong local structures in the graphs of these codes, which are detrimental to the code rate asymptotically. The proof method leads to an interesting necessary condition on the code structures which could achieve capacity with bounded decoding complexity. We also show that if a code sequence achieves a rate epsilon close to the channel capacity, the decoding complexity scales at least as O(log(1/epsilon).
cs/0702075
Firebird Database Backup by Serialized Database Table Dump
cs.DB
This paper presents a simple data dump and load utility for Firebird databases which mimics mysqldump in MySQL. This utility, fb_dump and fb_load, for dumping and loading respectively, retrieves each database table using kinterbasdb and serializes the data using marshal module. This utility has two advantages over the standard Firebird database backup utility, gbak. Firstly, it is able to backup and restore single database tables which might help to recover corrupted databases. Secondly, the output is in text-coded format (from marshal module) making it more resilient than a compressed text backup, as in the case of using gbak.
cs/0702077
Properties of Rank Metric Codes
cs.IT math.IT
This paper investigates general properties of codes with the rank metric. We first investigate asymptotic packing properties of rank metric codes. Then, we study sphere covering properties of rank metric codes, derive bounds on their parameters, and investigate their asymptotic covering properties. Finally, we establish several identities that relate the rank weight distribution of a linear code to that of its dual code. One of our identities is the counterpart of the MacWilliams identity for the Hamming metric, and it has a different form from the identity by Delsarte.
cs/0702081
Random Sentences from a Generalized Phrase-Structure Grammar Interpreter
cs.CL
In numerous domains in cognitive science it is often useful to have a source for randomly generated corpora. These corpora may serve as a foundation for artificial stimuli in a learning experiment (e.g., Ellefson & Christiansen, 2000), or as input into computational models (e.g., Christiansen & Dale, 2001). The following compact and general C program interprets a phrase-structure grammar specified in a text file. It follows parameters set at a Unix or Unix-based command-line and generates a corpus of random sentences from that grammar.
cs/0702082
Invariant template matching in systems with spatiotemporal coding: a vote for instability
cs.CV cs.AI
We consider the design of a pattern recognition that matches templates to images, both of which are spatially sampled and encoded as temporal sequences. The image is subject to a combination of various perturbations. These include ones that can be modeled as parameterized uncertainties such as image blur, luminance, translation, and rotation as well as unmodeled ones. Biological and neural systems require that these perturbations be processed through a minimal number of channels by simple adaptation mechanisms. We found that the most suitable mathematical framework to meet this requirement is that of weakly attracting sets. This framework provides us with a normative and unifying solution to the pattern recognition problem. We analyze the consequences of its explicit implementation in neural systems. Several properties inherent to the systems designed in accordance with our normative mathematical argument coincide with known empirical facts. This is illustrated in mental rotation, visual search and blur/intensity adaptation. We demonstrate how our results can be applied to a range of practical problems in template matching and pattern recognition.
cs/0702084
Performance of Ultra-Wideband Impulse Radio in Presence of Impulsive Interference
cs.IT math.IT
We analyze the performance of coherent impulsive-radio (IR) ultra-wideband (UWB) channel in presence of the interference generated by concurrent transmissions of the systems with the same impulsive radio. We derive a novel algorithm, using Monte-Carlo method, to calculate a lower bound on the rate that can be achieved using maximum-likelihood estimator. Using this bound we show that such a channel is very robust to interference, in contrast to the nearest-neighbor detector.
cs/0702085
Social Behaviours Applied to P2P Systems: An efficient Algorithm for Resource Organisation
cs.DC cs.IR
P2P systems are a great solution to the problem of distributing resources. The main issue of P2P networks is that searching and retrieving resources shared by peers is usually expensive and does not take into account similarities among peers. In this paper we present preliminary simulations of PROSA, a novel algorithm for P2P network structuring, inspired by social behaviours. Peers in PROSA self--organise in social groups of similar peers, called ``semantic--groups'', depending on the resources they are sharing. Such a network smoothly evolves to a small--world graph, where queries for resources are efficiently and effectively routed.
cs/0702091
Observable Graphs
cs.MA
An edge-colored directed graph is \emph{observable} if an agent that moves along its edges is able to determine his position in the graph after a sufficiently long observation of the edge colors. When the agent is able to determine his position only from time to time, the graph is said to be \emph{partly observable}. Observability in graphs is desirable in situations where autonomous agents are moving on a network and one wants to localize them (or the agent wants to localize himself) with limited information. In this paper, we completely characterize observable and partly observable graphs and show how these concepts relate to observable discrete event systems and to local automata. Based on these characterizations, we provide polynomial time algorithms to decide observability, to decide partial observability, and to compute the minimal number of observations necessary for finding the position of an agent. In particular we prove that in the worst case this minimal number of observations increases quadratically with the number of nodes in the graph. From this it follows that it may be necessary for an agent to pass through the same node several times before he is finally able to determine his position in the graph. We then consider the more difficult question of assigning colors to a graph so as to make it observable and we prove that two different versions of this problem are NP-complete.
cs/0702093
Secure Broadcasting
cs.IT math.IT
Wyner's wiretap channel is extended to parallel broadcast channels and fading channels with multiple receivers. In the first part of the paper, we consider the setup of parallel broadcast channels with one sender, multiple intended receivers, and one eavesdropper. We study the situations where the sender broadcasts either a common message or independent messages to the intended receivers. We derive upper and lower bounds on the common-message-secrecy capacity, which coincide when the users are reversely degraded. For the case of independent messages we establish the secrecy sum-capacity when the users are reversely degraded. In the second part of the paper we apply our results to fading channels: perfect channel state information of all intended receivers is known globally, whereas the eavesdropper channel is known only to her. For the common message case, a somewhat surprising result is proven: a positive rate can be achieved independently of the number of intended receivers. For independent messages, an opportunistic transmission scheme is presented that achieves the secrecy sum-capacity in the limit of large number of receivers. Our results are stated for a fast fading channel model. Extensions to the block fading model are also discussed.
cs/0702096
Overcoming Hierarchical Difficulty by Hill-Climbing the Building Block Structure
cs.NE cs.AI
The Building Block Hypothesis suggests that Genetic Algorithms (GAs) are well-suited for hierarchical problems, where efficient solving requires proper problem decomposition and assembly of solution from sub-solution with strong non-linear interdependencies. The paper proposes a hill-climber operating over the building block (BB) space that can efficiently address hierarchical problems. The new Building Block Hill-Climber (BBHC) uses past hill-climb experience to extract BB information and adapts its neighborhood structure accordingly. The perpetual adaptation of the neighborhood structure allows the method to climb the hierarchical structure solving successively the hierarchical levels. It is expected that for fully non deceptive hierarchical BB structures the BBHC can solve hierarchical problems in linearithmic time. Empirical results confirm that the proposed method scales almost linearly with the problem size thus clearly outperforms population based recombinative methods.
cs/0702097
Avoiding bias in cards cryptography
cs.CR cs.MA
We outline the need for stricter requirements for unconditionally secure cryptographic protocols inspired by the Russian Cards problem. A new requirement CA4 is proposed that checks for bias in single card occurrence in announcements consisting of alternatives for players' holdings of cards. This requirement CA4 is shown to be equivalent to an alternative requirement CA5. All announcements found to satisfy CA4 are 2-designs. We also show that all binary designs are 3-designs. Instead of avoiding bias in announcements produced by such protocols, one may as well apply unbiased protocols such that patterns in announcements become meaningless. We gave two examples of such protocols for card deal parameters (3,3,1), i.e. two of the players hold three cards, and the remaining player, playing the role of eavesdropper, holds a single card.
cs/0702099
Discrete Memoryless Interference and Broadcast Channels with Confidential Messages: Secrecy Rate Regions
cs.IT math.IT
We study information-theoretic security for discrete memoryless interference and broadcast channels with independent confidential messages sent to two receivers. Confidential messages are transmitted to their respective receivers with information-theoretic secrecy. That is, each receiver is kept in total ignorance with respect to the message intended for the other receiver. The secrecy level is measured by the equivocation rate at the eavesdropping receiver. In this paper, we present inner and outer bounds on secrecy capacity regions for these two communication systems. The derived outer bounds have an identical mutual information expression that applies to both channel models. The difference is in the input distributions over which the expression is optimized. The inner bound rate regions are achieved by random binning techniques. For the broadcast channel, a double-binning coding scheme allows for both joint encoding and preserving of confidentiality. Furthermore, we show that, for a special case of the interference channel, referred to as the switch channel, the two bound bounds meet. Finally, we describe several transmission schemes for Gaussian interference channels and derive their achievable rate regions while ensuring mutual information-theoretic secrecy. An encoding scheme in which transmitters dedicate some of their power to create artificial noise is proposed and shown to outperform both time-sharing and simple multiplexed transmission of the confidential messages.
cs/0702100
A Class of Multi-Channel Cosine Modulated IIR Filter Banks
cs.IT math.IT
This paper presents a class of multi-channel cosine-modulated filter banks satisfying the perfect reconstruction (PR) property using an IIR prototype filter. By imposing a suitable structure on the polyphase filter coefficients, we show that it is possible to greatly simplify the PR condition, while preserving the causality and stability of the system. We derive closed-form expressions for the synthesis filters and also study the numerical stability of the filter bank using frame theoretic bounds. Further, we show that it is possible to implement this filter bank with much lower number of arithmetic operations when compared to FIR filter banks with comparable performance. The filter bank's modular structure also lends itself to efficient VLSI implementation.
cs/0702101
An identity of Chernoff bounds with an interpretation in statistical physics and applications in information theory
cs.IT math.IT
An identity between two versions of the Chernoff bound on the probability a certain large deviations event, is established. This identity has an interpretation in statistical physics, namely, an isothermal equilibrium of a composite system that consists of multiple subsystems of particles. Several information--theoretic application examples, where the analysis of this large deviations probability naturally arises, are then described from the viewpoint of this statistical mechanical interpretation. This results in several relationships between information theory and statistical physics, which we hope, the reader will find insightful.
cs/0702102
Paging and Registration in Cellular Networks: Jointly Optimal Policies and an Iterative Algorithm
cs.IT cs.NI math.IT
This paper explores optimization of paging and registration policies in cellular networks. Motion is modeled as a discrete-time Markov process, and minimization of the discounted, infinite-horizon average cost is addressed. The structure of jointly optimal paging and registration policies is investigated through the use of dynamic programming for partially observed Markov processes. It is shown that there exist policies with a certain simple form that are jointly optimal, though the dynamic programming approach does not directly provide an efficient method to find the policies. An iterative algorithm for policies with the simple form is proposed and investigated. The algorithm alternates between paging policy optimization and registration policy optimization. It finds a pair of individually optimal policies, but an example is given showing that the policies need not be jointly optimal. Majorization theory and Riesz's rearrangement inequality are used to show that jointly optimal paging and registration policies are given for symmetric or Gaussian random walk models by the nearest-location-first paging policy and distance threshold registration policies.
cs/0702104
A Union Bound Approximation for Rapid Performance Evaluation of Punctured Turbo Codes
cs.IT math.IT
In this paper, we present a simple technique to approximate the performance union bound of a punctured turbo code. The bound approximation exploits only those terms of the transfer function that have a major impact on the overall performance. We revisit the structure of the constituent convolutional encoder and we develop a rapid method to calculate the most significant terms of the transfer function of a turbo encoder. We demonstrate that, for a large interleaver size, this approximation is very accurate. Furthermore, we apply our proposed method to a family of punctured turbo codes, which we call pseudo-randomly punctured codes. We conclude by emphasizing the benefits of our approach compared to those employed previously. We also highlight the advantages of pseudo-random puncturing over other puncturing schemes.
cs/0702105
The Simplest Solution to an Underdetermined System of Linear Equations
cs.IT math.IT
Consider a d*n matrix A, with d<n. The problem of solving for x in y=Ax is underdetermined, and has infinitely many solutions (if there are any). Given y, the minimum Kolmogorov complexity solution (MKCS) of the input x is defined to be an input z (out of many) with minimum Kolmogorov-complexity that satisfies y=Az. One expects that if the actual input is simple enough, then MKCS will recover the input exactly. This paper presents a preliminary study of the existence and value of the complexity level up to which such a complexity-based recovery is possible. It is shown that for the set of all d*n binary matrices (with entries 0 or 1 and d<n), MKCS exactly recovers the input for an overwhelming fraction of the matrices provided the Kolmogorov complexity of the input is O(d). A weak converse that is loose by a log n factor is also established for this case. Finally, we investigate the difficulty of finding a matrix that has the property of recovering inputs with complexity of O(d) using MKCS.
cs/0702106
Wild, Wild Wikis: A way forward
cs.IR
Wikis can be considered as public domain knowledge sharing system. They provide opportunity for those who may not have the privilege to publish their thoughts through the traditional methods. They are one of the fastest growing systems of online encyclopaedia. In this study, we consider the importance of wikis as a way of creating, sharing and improving public knowledge. We identify some of the problems associated with wikis to include, (a) identification of the identities of information and its creator (b) accuracy of information (c) justification of the credibility of authors (d) vandalism of quality of information (e) weak control over the contents. A solution to some of these problems is sought through the use of an annotation model. The model assumes that contributions in wikis can be seen as annotation to the initial document. It proposed a systematic control of contributors and contributions to the initiative and the keeping of records of what existed and what was done to initial documents. We believe that with this model, analysis can be done on the progress of wiki initiatives. We assumed that using this model, wikis can be better used for creation and sharing of knowledge for public use.
cs/0702107
AMIEDoT: An annotation model for document tracking and recommendation service
cs.IR
The primary objective of document annotation in whatever form, manual or electronic is to allow those who may not have control to original document to provide personal view on information source. Beyond providing personal assessment to original information sources, we are looking at a situation where annotation made can be used as additional source of information for document tracking and recommendation service. Most of the annotation tools existing today were conceived for their independent use with no reference to the creator of the annotation. We propose AMIEDoT (Annotation Model for Information Exchange and Document Tracking) an annotation model that can assist in document tracking and recommendation service. The model is based on three parameters in the acts of annotation. We believe that introducing document parameters, time and the parameters of the creator of annotation into an annotation process can be a dependable source to know, who used a document, when a document was used and for what a document was used for. Beyond document tracking, our model can be used in not only for selective dissemination of information but for recommendation services. AMIEDoT can also be used for information sharing and information reuse.
cs/0702108
Orthogonal Codes for Robust Low-Cost Communication
cs.IT math.IT
Orthogonal coding schemes, known to asymptotically achieve the capacity per unit cost (CPUC) for single-user ergodic memoryless channels with a zero-cost input symbol, are investigated for single-user compound memoryless channels, which exhibit uncertainties in their input-output statistical relationships. A minimax formulation is adopted to attain robustness. First, a class of achievable rates per unit cost (ARPUC) is derived, and its utility is demonstrated through several representative case studies. Second, when the uncertainty set of channel transition statistics satisfies a convexity property, optimization is performed over the class of ARPUC through utilizing results of minimax robustness. The resulting CPUC lower bound indicates the ultimate performance of the orthogonal coding scheme, and coincides with the CPUC under certain restrictive conditions. Finally, still under the convexity property, it is shown that the CPUC can generally be achieved, through utilizing a so-called mixed strategy in which an orthogonal code contains an appropriate composition of different nonzero-cost input symbols.
cs/0702109
AMIE: An annotation model for information research
cs.IR
The objective of most users for consulting any information database, information warehouse or the internet is to resolve one problem or the other. Available online or offline annotation tools were not conceived with the objective of assisting users in their bid to resolve a decisional problem. Apart from the objective and usage of annotation tools, how these tools are conceived and classified has implication on their usage. Several criteria have been used to categorize annotation concepts. Typically annotation are conceived based on how it affect the organization of document been considered for annotation or the organization of the resulting annotation. Our approach is annotation that will assist in information research for decision making. Annotation model for information exchange (AMIE) was conceived with the objective of information sharing and reuse.
cs/0702111
Informed Dynamic Scheduling for Belief-Propagation Decoding of LDPC Codes
cs.IT math.IT
Low-Density Parity-Check (LDPC) codes are usually decoded by running an iterative belief-propagation, or message-passing, algorithm over the factor graph of the code. The traditional message-passing schedule consists of updating all the variable nodes in the graph, using the same pre-update information, followed by updating all the check nodes of the graph, again, using the same pre-update information. Recently several studies show that sequential scheduling, in which messages are generated using the latest available information, significantly improves the convergence speed in terms of number of iterations. Sequential scheduling raises the problem of finding the best sequence of message updates. This paper presents practical scheduling strategies that use the value of the messages in the graph to find the next message to be updated. Simulation results show that these informed update sequences require significantly fewer iterations than standard sequential schedules. Furthermore, the paper shows that informed scheduling solves some standard trapping set errors. Therefore, it also outperforms traditional scheduling for a large numbers of iterations. Complexity and implementability issues are also addressed.
cs/0702112
The General Gaussian Multiple Access and Two-Way Wire-Tap Channels: Achievable Rates and Cooperative Jamming
cs.IT cs.CR math.IT
The General Gaussian Multiple Access Wire-Tap Channel (GGMAC-WT) and the Gaussian Two-Way Wire-Tap Channel (GTW-WT) are considered. In the GGMAC-WT, multiple users communicate with an intended receiver in the presence of an eavesdropper who receives their signals through another GMAC. In the GTW-WT, two users communicate with each other over a common Gaussian channel, with an eavesdropper listening through a GMAC. A secrecy measure that is suitable for this multi-terminal environment is defined, and achievable secrecy rate regions are found for both channels. For both cases, the power allocations maximizing the achievable secrecy sum-rate are determined. It is seen that the optimum policy may prevent some terminals from transmission in order to preserve the secrecy of the system. Inspired by this construct, a new scheme, \ital{cooperative jamming}, is proposed, where users who are prevented from transmitting according to the secrecy sum-rate maximizing power allocation policy "jam" the eavesdropper, thereby helping the remaining users. This scheme is shown to increase the achievable secrecy sum-rate. Overall, our results show that in multiple-access scenarios, users can help each other to collectively achieve positive secrecy rates. In other words, cooperation among users can be invaluable for achieving secrecy for the system.
cs/0702115
Guessing based on length functions
cs.IT cs.CR math.IT
A guessing wiretapper's performance on a Shannon cipher system is analyzed for a source with memory. Close relationships between guessing functions and length functions are first established. Subsequently, asymptotically optimal encryption and attack strategies are identified and their performances analyzed for sources with memory. The performance metrics are exponents of guessing moments and probability of large deviations. The metrics are then characterized for unifilar sources. Universal asymptotically optimal encryption and attack strategies are also identified for unifilar sources. Guessing in the increasing order of Lempel-Ziv coding lengths is proposed for finite-state sources, and shown to be asymptotically optimal. Finally, competitive optimality properties of guessing in the increasing order of description lengths and Lempel-Ziv coding lengths are demonstrated.
cs/0702118
Interpolation-based Decoding of Alternant Codes
cs.IT math.IT
We formulate the classical decoding algorithm of alternant codes afresh based on interpolation as in Sudan's list decoding of Reed-Solomon codes, and thus get rid of the key equation and the linear recurring sequences in the theory. The result is a streamlined exposition of the decoding algorithm using a bit of the theory of Groebner bases of modules.
cs/0702122
Transmitter and Precoding Order Optimization for Nonlinear Downlink Beamforming
cs.IT math.IT
The downlink of a multiple-input multiple output (MIMO) broadcast channel (BC) is considered, where each receiver is equipped with a single antenna and the transmitter performs nonlinear Dirty-Paper Coding (DPC). We present an efficient algorithm that finds the optimum transmit filters and power allocation as well as the optimum precoding order(s) possibly affording time-sharing between individual DPC orders. Subsequently necessary and sufficient conditions for the optimality of an arbitrary precoding order are derived. Based on these we propose a suboptimal algorithm showing excellent performance and having low complexity.
cs/0702126
Efficient Searching and Retrieval of Documents in PROSA
cs.DC cs.IR
Retrieving resources in a distributed environment is more difficult than finding data in centralised databases. In the last decade P2P system arise as new and effective distributed architectures for resource sharing, but searching in such environments could be difficult and time-consuming. In this paper we discuss efficiency of resource discovery in PROSA, a self-organising P2P system heavily inspired by social networks. All routing choices in PROSA are made locally, looking only at the relevance of the next peer to each query. We show that PROSA is able to effectively answer queries for rare documents, forwarding them through the most convenient path to nodes that much probably share matching resources. This result is heavily related to the small-world structure that naturally emerges in PROSA.
cs/0702127
Exploiting social networks dynamics for P2P resource organisation
cs.DC cs.IR
In this paper we present a formal description of PROSA, a P2P resource management system heavily inspired by social networks. Social networks have been deeply studied in the last two decades in order to understand how communities of people arise and grow. It is a widely known result that networks of social relationships usually evolves to small-worlds, i.e. networks where nodes are strongly connected to neighbours and separated from all other nodes by a small amount of hops. This work shows that algorithms implemented into PROSA allow to obtain an efficient small-world P2P network.
cs/0702130
Syndrome Decoding of Reed-Solomon Codes Beyond Half the Minimum Distance based on Shift-Register Synthesis
cs.IT math.IT
In this paper, a new approach for decoding low-rate Reed-Solomon codes beyond half the minimum distance is considered and analyzed. Unlike the Sudan algorithm published in 1997, this new approach is based on multi-sequence shift-register synthesis, which makes it easy to understand and simple to implement. The computational complexity of this shift-register based algorithm is of the same order as the complexity of the well-known Berlekamp-Massey algorithm. Moreover, the error correcting radius coincides with the error correcting radius of the original Sudan algorithm, and the practical decoding performance observed on a q-ary symmetric channel (QSC) is virtually identical to the decoding performance of the Sudan algorithm. Bounds for the failure and error probability as well as for the QSC decoding performance of the new algorithm are derived, and the performance is illustrated by means of examples.
cs/0702131
AICA: a New Pair Force Evaluation Method for Parallel Molecular Dynamics in Arbitrary Geometries
cs.CE cs.DC
A new algorithm for calculating intermolecular pair forces in Molecular Dynamics (MD) simulations on a distributed parallel computer is presented. The Arbitrary Interacting Cells Algorithm (AICA) is designed to operate on geometrical domains defined by an unstructured, arbitrary polyhedral mesh, which has been spatially decomposed into irregular portions for parallelisation. It is intended for nano scale fluid mechanics simulation by MD in complex geometries, and to provide the MD component of a hybrid MD/continuum simulation. AICA has been implemented in the open-source computational toolbox OpenFOAM, and verified against a published MD code.
cs/0702132
Uplink Capacity and Interference Avoidance for Two-Tier Femtocell Networks
cs.NI cs.IT math.IT
Two-tier femtocell networks-- comprising a conventional macrocellular network plus embedded femtocell hotspots-- offer an economically viable solution to achieving high cellular user capacity and improved coverage. With universal frequency reuse and DS-CDMA transmission however, the ensuing cross-tier cochannel interference (CCI) causes unacceptable outage probability. This paper develops an uplink capacity analysis and interference avoidance strategy in such a two-tier CDMA network. We evaluate a network-wide area spectral efficiency metric called the \emph{operating contour (OC)} defined as the feasible combinations of the average number of active macrocell users and femtocell base stations (BS) per cell-site that satisfy a target outage constraint. The capacity analysis provides an accurate characterization of the uplink outage probability, accounting for power control, path-loss and shadowing effects. Considering worst case CCI at a corner femtocell, results reveal that interference avoidance through a time-hopped CDMA physical layer and sectorized antennas allows about a 7x higher femtocell density, relative to a split spectrum two-tier network with omnidirectional femtocell antennas. A femtocell exclusion region and a tier selection based handoff policy offers modest improvements in the OCs. These results provide guidelines for the design of robust shared spectrum two-tier networks.
cs/0702138
On the Maximal Diversity Order of Spatial Multiplexing with Transmit Antenna Selection
cs.IT math.IT
Zhang et. al. recently derived upper and lower bounds on the achievable diversity of an N_R x N_T i.i.d. Rayleigh fading multiple antenna system using transmit antenna selection, spatial multiplexing and a linear receiver structure. For the case of L = 2 transmitting (out of N_T available) antennas the bounds are tight and therefore specify the maximal diversity order. For the general case with L <= min(N_R,N_T) transmitting antennas it was conjectured that the maximal diversity is (N_T-L+1)(N_R-L+1) which coincides with the lower bound. Herein, we prove this conjecture for the zero forcing and zero forcing decision feedback (with optimal detection ordering) receiver structures.
cs/0702142
An Optimal Linear Time Algorithm for Quasi-Monotonic Segmentation
cs.DS cs.DB
Monotonicity is a simple yet significant qualitative characteristic. We consider the problem of segmenting an array in up to K segments. We want segments to be as monotonic as possible and to alternate signs. We propose a quality metric for this problem, present an optimal linear time algorithm based on novel formalism, and compare experimentally its performance to a linear time top-down regression algorithm. We show that our algorithm is faster and more accurate. Applications include pattern recognition and qualitative modeling.
cs/0702143
Attribute Value Reordering For Efficient Hybrid OLAP
cs.DB
The normalization of a data cube is the ordering of the attribute values. For large multidimensional arrays where dense and sparse chunks are stored differently, proper normalization can lead to improved storage efficiency. We show that it is NP-hard to compute an optimal normalization even for 1x3 chunks, although we find an exact algorithm for 1x2 chunks. When dimensions are nearly statistically independent, we show that dimension-wise attribute frequency sorting is an optimal normalization and takes time O(d n log(n)) for data cubes of size n^d. When dimensions are not independent, we propose and evaluate several heuristics. The hybrid OLAP (HOLAP) storage mechanism is already 19%-30% more efficient than ROLAP, but normalization can improve it further by 9%-13% for a total gain of 29%-44% over ROLAP.
cs/0702144
Slope One Predictors for Online Rating-Based Collaborative Filtering
cs.DB cs.AI
Rating-based collaborative filtering is the process of predicting how a user would rate a given item from other user ratings. We propose three related slope one schemes with predictors of the form f(x) = x + b, which precompute the average difference between the ratings of one item and another for users who rated both. Slope one algorithms are easy to implement, efficient to query, reasonably accurate, and they support both online queries and dynamic updates, which makes them good candidates for real-world systems. The basic slope one scheme is suggested as a new reference scheme for collaborative filtering. By factoring in items that a user liked separately from items that a user disliked, we achieve results competitive with slower memory-based schemes over the standard benchmark EachMovie and Movielens data sets while better fulfilling the desiderata of CF applications.
cs/0702146
A Local Tree Structure is NOT Sufficient for the Local Optimality of Message-Passing Decoding in Low Density Parity Check Codes
cs.IT math.IT
We address the problem,`Is a local tree structure sufficient for the local optimality of message passing algorithm in low density parity check codes?'.It is shown that the answer is negative. Using this observation, we pinpoint a flaw in the proof of Theorem 1 in the paper `The Capacity of Low-Density Parity-Check Codes Under Message-Passing Decoding' by Thomas J. Richardson and R\"udiger L.Urbanke\cite{RUCapacity}. We further provide a new proof of that theorem based on a different argument.
cs/0702147
On the Complexity of Exact Maximum-Likelihood Decoding for Asymptotically Good Low Density Parity Check Codes
cs.IT math.IT
Since the classical work of Berlekamp, McEliece and van Tilborg, it is well known that the problem of exact maximum-likelihood (ML) decoding of general linear codes is NP-hard. In this paper, we show that exact ML decoding of a classs of asymptotically good error correcting codes--expander codes, a special case of low density parity check (LDPC) codes--over binary symmetric channels (BSCs) is possible with an expected polynomial complexity. More precisely, for any bit-flipping probability, $p$, in a nontrivial range, there exists a rate region of non-zero support and a family of asymptotically good codes, whose error probability decays exponentially in coding length $n$, for which ML decoding is feasible in expected polynomial time. Furthermore, as $p$ approaches zero, this rate region approaches the channel capacity region. The result is based on the existence of polynomial-time suboptimal decoding algorithms that provide an ML certificate and the ability to compute the probability that the suboptimal decoder yields the ML solution. One such ML certificate decoder is the LP decoder of Feldman; we also propose a more efficient $O(n^2)$ algorithm based on the work of Sipser and Spielman and the Ford-Fulkerson algorithm. The results can be extended to AWGN channels and suggest that it may be feasible to eliminate the error floor phenomenon associated with message-passage decoding of LDPC codes in the high SNR regime. Finally, we observe that the argument of Berlekamp, McEliece and van Tilborg can be used to show that ML decoding of the considered class of codes constructed from LDPC codes with regular left degree, of which the considered expander codes are a special case, remains NP-hard; thus giving an interesting contrast between the worst-case and expected complexities.
cs/0702148
Linking Microscopic and Macroscopic Models for Evolution: Markov Chain Network Training and Conservation Law Approximations
cs.CE cs.IT cs.NA cs.NE math.IT
In this paper, a general framework for the analysis of a connection between the training of artificial neural networks via the dynamics of Markov chains and the approximation of conservation law equations is proposed. This framework allows us to demonstrate an intrinsic link between microscopic and macroscopic models for evolution via the concept of perturbed generalized dynamic systems. The main result is exemplified with a number of illustrative examples where efficient numerical approximations follow directly from network-based computational models, viewed here as Markov chain approximations. Finally, stability and consistency conditions of such computational models are discussed.
cs/0702149
Coupling Control and Human-Centered Automation in Mathematical Models of Complex Systems
cs.CE cs.AI cs.HC cs.IT math.IT
In this paper we analyze mathematically how human factors can be effectively incorporated into the analysis and control of complex systems. As an example, we focus our discussion around one of the key problems in the Intelligent Transportation Systems (ITS) theory and practice, the problem of speed control, considered here as a decision making process with limited information available. The problem is cast mathematically in the general framework of control problems and is treated in the context of dynamically changing environments where control is coupled to human-centered automation. Since in this case control might not be limited to a small number of control settings, as it is often assumed in the control literature, serious difficulties arise in the solution of this problem. We demonstrate that the problem can be reduced to a set of Hamilton-Jacobi-Bellman equations where human factors are incorporated via estimations of the system Hamiltonian. In the ITS context, these estimations can be obtained with the use of on-board equipment like sensors/receivers/actuators, in-vehicle communication devices, etc. The proposed methodology provides a way to integrate human factor into the solving process of the models for other complex dynamic systems.
cs/0702150
A note on rate-distortion functions for nonstationary Gaussian autoregressive processes
cs.IT math.IT
Source coding theorems and Shannon rate-distortion functions were studied for the discrete-time Wiener process by Berger and generalized to nonstationary Gaussian autoregressive processes by Gray and by Hashimoto and Arimoto. Hashimoto and Arimoto provided an example apparently contradicting the methods used in Gray, implied that Gray's rate-distortion evaluation was not correct in the nonstationary case, and derived a new formula that agreed with previous results for the stationary case and held in the nonstationary case. In this correspondence it is shown that the rate-distortion formulas of Gray and Hashimoto and Arimoto are in fact consistent and that the example of of Hashimoto and Arimoto does not form a counter example to the methods or results of the earlier paper. Their results do provide an alternative, but equivalent, formula for the rate-distortion function in the nonstationary case and they provide a concrete example that the classic Kolmogorov formula differs from the autoregressive formula when the autoregressive source is not stationary. Some observations are offered on the different versions of the Toeplitz asymptotic eigenvalue distribution theorem used in the two papers to emphasize how a slight modification of the classic theorem avoids the problems with certain singularities.
cs/0702154
On the Capacity of the Single Source Multiple Relay Single Destination Mesh Network
cs.IT cs.NI math.IT
In this paper, we derive the information theoretic capacity of a special class of mesh networks. A mesh network is a heterogeneous wireless network in which the transmission among power limited nodes is assisted by powerful relays, which use the same wireless medium. We investigate the mesh network when there is one source, one destination, and multiple relays, which we call the single source multiple relay single destination (SSMRSD) mesh network. We derive the asymptotic capacity of the SSMRSD mesh network when the relay powers grow to infinity. Our approach is as follows. We first look at an upper bound on the information theoretic capacity of these networks in a Gaussian setting. We then show that this bound is achievable asymptotically using the compress-and-forward strategy for the multiple relay channel. We also perform numerical computations for the case when the relays have finite powers. We observe that even when the relay power is only a few times larger than the source power, the compress-and-forward rate gets close to the capacity. The results indicate the value of cooperation in wireless mesh networks. The capacity characterization quantifies how the relays can cooperate, using the compress-and-forward strategy, to either conserve node energy or to increase transmission rate.
cs/0702159
Perfect Hashing for Data Management Applications
cs.DS cs.DB
Perfect hash functions can potentially be used to compress data in connection with a variety of data management tasks. Though there has been considerable work on how to construct good perfect hash functions, there is a gap between theory and practice among all previous methods on minimal perfect hashing. On one side, there are good theoretical results without experimentally proven practicality for large key sets. On the other side, there are the theoretically analyzed time and space usage algorithms that assume that truly random hash functions are available for free, which is an unrealistic assumption. In this paper we attempt to bridge this gap between theory and practice, using a number of techniques from the literature to obtain a novel scheme that is theoretically well-understood and at the same time achieves an order-of-magnitude increase in performance compared to previous ``practical'' methods. This improvement comes from a combination of a novel, theoretically optimal perfect hashing scheme that greatly simplifies previous methods, and the fact that our algorithm is designed to make good use of the memory hierarchy. We demonstrate the scalability of our algorithm by considering a set of over one billion URLs from the World Wide Web of average length 64, for which we construct a minimal perfect hash function on a commodity PC in a little more than 1 hour. Our scheme produces minimal perfect hash functions using slightly more than 3 bits per key. For perfect hash functions in the range $\{0,...,2n-1\}$ the space usage drops to just over 2 bits per key (i.e., one bit more than optimal for representing the key). This is significantly below of what has been achieved previously for very large values of $n$.
cs/0702161
Perfectly Secure Steganography: Capacity, Error Exponents, and Code Constructions
cs.IT cs.CR math.IT
An analysis of steganographic systems subject to the following perfect undetectability condition is presented in this paper. Following embedding of the message into the covertext, the resulting stegotext is required to have exactly the same probability distribution as the covertext. Then no statistical test can reliably detect the presence of the hidden message. We refer to such steganographic schemes as perfectly secure. A few such schemes have been proposed in recent literature, but they have vanishing rate. We prove that communication performance can potentially be vastly improved; specifically, our basic setup assumes independently and identically distributed (i.i.d.) covertext, and we construct perfectly secure steganographic codes from public watermarking codes using binning methods and randomized permutations of the code. The permutation is a secret key shared between encoder and decoder. We derive (positive) capacity and random-coding exponents for perfectly-secure steganographic systems. The error exponents provide estimates of the code length required to achieve a target low error probability. We address the potential loss in communication performance due to the perfect-security requirement. This loss is the same as the loss obtained under a weaker order-1 steganographic requirement that would just require matching of first-order marginals of the covertext and stegotext distributions. Furthermore, no loss occurs if the covertext distribution is uniform and the distortion metric is cyclically symmetric; steganographic capacity is then achieved by randomized linear codes. Our framework may also be useful for developing computationally secure steganographic systems that have near-optimal communication performance.