Pervasive services applications often employ networked sensors,
devices and appliances to build intelligent and adaptable environments, such
as Smart Homes. One of the most significant emergent problems in the
deployment of such applications is conflicting sensors information. The
system is required to decipher the true context of ambiguous or conflicting
data in order to efficiently assimilate context-awareness and subsequently
ensure accurate adaptability to suit the application space. To-date, there
has been speculation as to the optimal method to disambiguate conflicting
data; citing the use of ”argumentation” based reasoning to resolve conflict
situations as a theoretical solution. This chapter presents the first known
implementation of argumentation based conflict resolution for pervasive
services computing. It proves that the concept is feasible, accurate and
efficient, through simulated deployment on a range of conflict scenarios. The
prototype is based on SOA4D built upon the OSGi platform and implements
DPWS; and is capable of resolving conflicting data gathered from up to
10 sensors in approximately 2.5 seconds. In effect, this work realises the
potential of argumentation theory to solve real-world problems in services
computing.
Keywords: Argumentation Theory, Conflict Resolution, Context
Information, Service-oriented Architecture, Quality of Context, Pervasive
Computing, Argumentation-based Decision Making, Computational
Argumentation, Intelligent Agents, Multi-agent Systems.
