zuh/ITDataset · Datasets at Hugging Face

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Challenges in Ubiquitous Data Management
Improved hardware and networking are clearly central to the development of
ubiquitous computing, but an equally important and difficult set of challenges revolve
around Data Management [AK93]. In order for computing to fade into the
background while supporting more and more activities, the data required to support
those activities must be reliably and efficiently stored, queried, and delivered.
Traditional approaches to data management such as caching, concurrency control,
query processing, etc. need to be adapted to the requirements and restrictions of
ubiquitous computing environments. These include resource limitations, varying and
intermittent connectivity, mobile users, and dynamic collaborations.

In this paper we first discuss the main characteristics of applications that
ubiquitous computing aims to support and then focus on the requirements that such
applications impose on data management technology. We then examine several
different aspects of data management and how they are being adapted to these new
requirements.

Applications and Data Management Requirements

While there is wide agreement on the great potential of ubiquitous computing, it is not
yet clear what the killer applications (i.e., the uses that will result in widespread
adoption) will be. Many researchers and product developers have created example
scenarios to demonstrate the potential of the technology. Due to the integrated and
universal nature of ubiquitous computing, these scenarios tend to include a large
number of functions rather than any one single application. Thus, some in industry
have begun to talk in terms of delivering a certain type of user experience rather
than a particular application or suite of applications. These scenarios tend to involve
users with several portable devices, moving between different environments (e.g.,
home, car, office, conference). The devices typically take an active (and often
annoying) role in reminding the user of various appointments and tasks that are due,
provide access to any and all information that may be relevant to these tasks, and
facilitate communication among groups of individuals involved in the tasks.

Categories of Functionality

Rather than specify yet another such scenario, it is perhaps more useful to categorize
the functionalities that such scenarios imply. This categorization can then be
examined to determine the requirements that are imposed on data management. The
functionalities can be classified into the following:

1) Support for mobility the compactness of the devices combined with
wireless communication means that the devices can be used in mobile
situations. Thus, existing applications must be able to operate in varied
and dynamic communication and computation environments, possibly moving from one network or service provider to another. Furthermore,
new applications that are location-centric will also be developed.

2) Context awareness if devices become truly ubiquitous, then they will
be used constantly in a wide range of continually changing situations.
For the devices to be truly helpful, they must be aware of the
environment as well as the tasks that the user is performing or will be
performing in the near future. Context aware applications range from
intelligent notification systems that inform the user of (hopefully)
important events or data, to smart spaces , that is, rooms or
environments that adapt based on who is present and what they are
doing.

3) Support for collaboration another key theme of ubiquitous computing
applications is the support of groups of people. This support consists of
communications and conferencing as well as the storage, maintenance,
delivery, and presentation of shared data. Collaborations may be
performed in real-time, if all of the participants are available, or may be
done asynchronously otherwise. In addition to supporting on-going
collaboration, access to and analysis of traces of past activities is also
required.

Adaptivity and User Interaction

These functionalities provide a host of challenges for data management techniques,
but one requirement is present across all of them, namely, the need for adaptivity.
Mobile users and devices, changing contexts, and dynamic groups all impose
requirements for flexibility and responsiveness that are simply not addressed by most
traditional data management techniques. Thus, adaptivity is a common theme of the
techniques that we discuss in the remainder of the paper.

It is also important to note that because ubiquitous computing is intended to
augment human capabilities in the execution of various tasks, the nature of these
applications is that the user is typically interacting in real-time with the computers.
We are able to exploit this fact as part of the solution to adaptivity by, in some cases,
depending on the users to make dynamic choices or to cope with some degree of
ambiguity. A concrete example of such a design choice is the way that many
groupware systems handle concurrent access and update to shared data. Rather than
impose rules that restrict the types and degrees of interaction that users can have, as is
done by concurrency control mechanisms in traditional database systems, a
groupware data manager will typically impose less stringent rules. The relaxation of
these rules limits the extent to which the system can autonomously handle conflicts.
Thus, such systems typically handle whatever cases they can, and when they detect a
conflict that cannot be handled automatically, they simply inform the user(s) that the
conflict has occurred, and allow them to resolve it based on their knowledge of the
situation. Thus, having users in the loop can be leveraged to provide more adaptive
and flexible systems.

Challenges in Ubiquitous Data Management

Requirements Due to Mobility

Other data management requirements are less universal across the three categories but
yet must be addressed in order to support a comprehensive ubiquitous computing
environment. For example, the issue of mobility raises a number of issues. First, the
fact that the terminals (i.e. devices) are constantly moving, and often have limited
storage capacity means that a ubiquitous computing system must be able to deliver

Challenges in Ubiquitous Data Management

Improved hardware and networking are clearly central to the development of

ubiquitous computing, but an equally important and difficult set of challenges revolve

around Data Management [AK93]. In order for computing to fade into the

background while supporting more and more activities, the data required to support

those activities must be reliably and efficiently stored, queried, and delivered.

Traditional approaches to data management such as caching, concurrency control,

query processing, etc. need to be adapted to the requirements and restrictions of

ubiquitous computing environments. These include resource limitations, varying and

intermittent connectivity, mobile users, and dynamic collaborations.

In this paper we first discuss the main characteristics of applications that

ubiquitous computing aims to support and then focus on the requirements that such

applications impose on data management technology. We then examine several

different aspects of data management and how they are being adapted to these new

requirements.

Applications and Data Management Requirements

While there is wide agreement on the great potential of ubiquitous computing, it is not

yet clear what the killer applications (i.e., the uses that will result in widespread

adoption) will be. Many researchers and product developers have created example

scenarios to demonstrate the potential of the technology. Due to the integrated and

universal nature of ubiquitous computing, these scenarios tend to include a large

number of functions rather than any one single application. Thus, some in industry

have begun to talk in terms of delivering a certain type of user experience rather

than a particular application or suite of applications. These scenarios tend to involve

users with several portable devices, moving between different environments (e.g.,

home, car, office, conference). The devices typically take an active (and often

annoying) role in reminding the user of various appointments and tasks that are due,

provide access to any and all information that may be relevant to these tasks, and

facilitate communication among groups of individuals involved in the tasks.

Categories of Functionality

Rather than specify yet another such scenario, it is perhaps more useful to categorize

the functionalities that such scenarios imply. This categorization can then be

examined to determine the requirements that are imposed on data management. The

functionalities can be classified into the following:

1) Support for mobility the compactness of the devices combined with

wireless communication means that the devices can be used in mobile

situations. Thus, existing applications must be able to operate in varied

and dynamic communication and computation environments, possibly moving from one network or service provider to another. Furthermore,

new applications that are location-centric will also be developed.

2) Context awareness if devices become truly ubiquitous, then they will

be used constantly in a wide range of continually changing situations.

For the devices to be truly helpful, they must be aware of the

environment as well as the tasks that the user is performing or will be

performing in the near future. Context aware applications range from

intelligent notification systems that inform the user of (hopefully)

important events or data, to smart spaces , that is, rooms or

environments that adapt based on who is present and what they are

doing.

3) Support for collaboration another key theme of ubiquitous computing

applications is the support of groups of people. This support consists of

communications and conferencing as well as the storage, maintenance,

delivery, and presentation of shared data. Collaborations may be

performed in real-time, if all of the participants are available, or may be

done asynchronously otherwise. In addition to supporting on-going

collaboration, access to and analysis of traces of past activities is also

required.

Adaptivity and User Interaction

These functionalities provide a host of challenges for data management techniques,

but one requirement is present across all of them, namely, the need for adaptivity.

Mobile users and devices, changing contexts, and dynamic groups all impose

requirements for flexibility and responsiveness that are simply not addressed by most

traditional data management techniques. Thus, adaptivity is a common theme of the

techniques that we discuss in the remainder of the paper.

It is also important to note that because ubiquitous computing is intended to

augment human capabilities in the execution of various tasks, the nature of these

applications is that the user is typically interacting in real-time with the computers.

We are able to exploit this fact as part of the solution to adaptivity by, in some cases,

depending on the users to make dynamic choices or to cope with some degree of

ambiguity. A concrete example of such a design choice is the way that many

groupware systems handle concurrent access and update to shared data. Rather than

impose rules that restrict the types and degrees of interaction that users can have, as is

done by concurrency control mechanisms in traditional database systems, a

groupware data manager will typically impose less stringent rules. The relaxation of

these rules limits the extent to which the system can autonomously handle conflicts.

Thus, such systems typically handle whatever cases they can, and when they detect a

conflict that cannot be handled automatically, they simply inform the user(s) that the

conflict has occurred, and allow them to resolve it based on their knowledge of the

situation. Thus, having users in the loop can be leveraged to provide more adaptive

and flexible systems.

Challenges in Ubiquitous Data Management

Requirements Due to Mobility

Other data management requirements are less universal across the three categories but

yet must be addressed in order to support a comprehensive ubiquitous computing

environment. For example, the issue of mobility raises a number of issues. First, the

fact that the terminals (i.e. devices) are constantly moving, and often have limited

storage capacity means that a ubiquitous computing system must be able to deliver