Issue No. 07 - July (2007 vol. 18)
Swaroop Kalasapur , IEEE
Mohan Kumar , IEEE
Behrooz A. Shirazi , IEEE
<p><b>Abstract</b>—Service-oriented architectures (SOAs) promise to provide transparency to resource access by exposing the resources available as services. SOAs have been employed within pervasive computing systems to provide essential support to user tasks by creating services representing the available resources. The mechanism of combining two or more basic services into a possibly complex service is known as service composition. Existing solutions to service composition employ a template-matching approach, where the user needs are expressed as a request template, and through composition, a system would identify services to populate the entities within the request template. However, with the dynamism involved in pervasive environments, the user needs have to be met by exploiting available resources, even when an exact match does not exist. In this paper, we present a novel service composition mechanism for pervasive computing. We employ the service-oriented middleware platform called Pervasive Information Communities Organization (PICO) to model and represent resources as services. The proposed service composition mechanism models services as directed attributed graphs, maintains a repository of service graphs, and dynamically combines multiple basic services into complex services. Further, we present a hierarchical overlay structure created among the devices to exploit the resource unevenness, resulting in the capability of providing essential service-related support to resource-poor devices. Results of extensive simulation studies are presented to illustrate the suitability of the proposed mechanism in meeting the challenges of pervasive computing—user mobility, heterogeneity, and the uncertain nature of involved resources.</p>
Pervasive computing, dynamic service composition, graph models, middleware, heterogeneous devices.
S. Kalasapur, B. A. Shirazi and M. Kumar, "Dynamic Service Composition in Pervasive Computing," in IEEE Transactions on Parallel & Distributed Systems, vol. 18, no. , pp. 907-918, 2007.