DocumentCode
2238461
Title
an affinity-driven clustering approach for service discovery and composition for pervasive computing
Author
Gaber, J. ; Bakhouya, Mohamed
Author_Institution
Lab. Syst. et Transp., Univ. de Technologie de Belfort-Montbeliard, Belfort
fYear
2006
fDate
26-29 June 2006
Firstpage
277
Lastpage
280
Abstract
Pervasive computing is a new paradigm with a goal to provide computing and communication services all the time and everywhere. In this paper, a service emergence model for the implementation of pervasive computing applications is presented. In this model, ad hoc or composite services are represented by an organization or group of autonomous agents. Agents establish relationships based on affinities. Affinity corresponds to the adequacy with which two services could bind to create a composed service or to point out a similar service. These affinities are adjusted or reinforced by user satisfaction regarding the provided service and dynamic network condition changes. Simulations of this proposed service emergence model with NS2 are also presented
Keywords
mobile agents; ubiquitous computing; affinity-driven clustering approach; autonomous agents; composite services; mobile ad hoc network; pervasive computing; reinforcement learning; service composition; service discovery; service emergence model; user satisfaction; Pervasive computing;
fLanguage
English
Publisher
ieee
Conference_Titel
Pervasive Services, 2006 ACS/IEEE International Conference on
Conference_Location
Lyon
Print_ISBN
1-4244-0237-9
Type
conf
DOI
10.1109/PERSER.2006.1652241
Filename
1652241
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