Information Technology Reference
In-Depth Information
INTRODUCTION
cern about cooperation is lacking. As the required
pervasive services are getting larger and more
complex, cooperation among pervasive objects
becomes increasingly important. Accordingly, it is
necessary to raise concern about cooperation in a
pervasive environment. For example, it can be the
cooperation-based service providing scheme, the
configuration of cooperative organizations, coop-
erative behaviors between pervasive objects, etc.
The ultimate objective of our work is to de-
sign and develop pervasive computing systems
efficiently which provide services by using coop-
eration among objects that already exist within a
given environment. Existing approaches, includ-
ing multi-agent approaches and other pervasive
system development approaches, are not adequate
for our purpose. Therefore, in this chapter, we
introduce community computing, a new ap-
proach to design and develop such a cooperative
pervasive computing system. In order to meet
our objective, we are employing the concept of
community. In community computing, community
is a high-level abstract concept for organizing,
managing, operating, and repairing groups of
computing elements in a pervasive environment.
Using the community concept, we are able to meet
all requirements of pervasive computing. First of
all, community computing can adapt to changes
in runtime by dynamic creation of a goal-driven
community and dynamic binding of the roles in
the community to actual objects. Secondly, com-
munity computing supports dynamic cooperation
among objects through dynamic decisions about
cooperative behavior and dynamic injection, a
cooperation process into member objects. Also,
we can guarantee proper separation of concerns
in community computing. In the community com-
puting models, group concerns are discriminated
from concerns about individual objects. Finally,
community computing supports the scalability of
services by merging of communities or the scal-
ability of systems by merging of societies. (See
section 3 for the definition of society).
Since ubiquitous computing was articulated by
Mark Weiser in 1991 (Weiser, 1991), many re-
searchers have attempted to realize the potential
for diverse pervasive services. As we surveyed
existing research, we were able to find the unique
characteristics of pervasive computing. First of
all, a pervasive computing system is composed
of highly heterogeneous computing elements
(Weiser, 1991; Kindberg, 2002). As computing
elements have mobility and their status changes
frequently, the environment of a pervasive system
is dynamically changing. In such a dynamic envi-
ronment, predictable or unpredictable pervasive
services are dynamically requested. Among all
characteristics, what we concentrate on the most
is that many pervasive services can be provided by
cooperation among heterogeneous smart objects
rather than by the ability of a single smart object.
In order to design and develop a pervasive sys-
tem having all such characteristics, we surveyed
existing approaches, but they were not perfectly
adequate to do it.
In the PICO Project, community computing
was introduced as a framework for cooperation
among agents in a pervasive environment (Ku-
mar, 2003). However, in this approach, some
room was left to develop the pervasive systems
providing services by using cooperation among
intelligent devices. Most of all, there is no well-
defined formal model. The PICO Project and
Active Space Project have introduced a similar
view of pervasive services to our community
computing, but they provide no concrete model
to represent such pervasive systems. Accordingly,
to design cooperation among agents, PICO needs
an abstraction model to describe cooperation. In
order to find an appropriate model, we surveyed
quite a few models, especially focusing on multi-
agent models. It should be noted, however, that
there are some differences between multi-agent
approaches and our approach for cooperative
systems. Furthermore, detailed and strong con-
Search WWH ::
Custom Search