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| Content Provider | IEEE Xplore Digital Library | 
|---|---|
| Author | Hassnaoui, A. Bakhouya, M. Gaber, J. | 
| Copyright Year | 2006 | 
| Description | Author affiliation: Institut National des Telecommunications, France (Hassnaoui, A.) | 
| 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. Inspired by natural immune system concepts, the model allows the emergence of ad hoc services on the fly according to dynamically changing context environments such as computing context and user context. In this model, ad hoc or composite services are represented by an organization or group of autonomous agents. Agents establish relationships based on affinities to form groups of agents to provide the composite services. Affinities are parameters that represent priorities between agents. They help to distinguish between agents that can satisfy certain conditions or criteria. Affinity adjustments are based on two level of satisfaction. The first level is a local satisfaction depending on available services offered by neighboring agents together with respect to dynamic changes in network resources. The second level is a global satisfaction determined by the user satisfaction regarding the end service provided. | 
| Starting Page | 15 | 
| Ending Page | 15 | 
| File Size | 235557 | 
| Page Count | 1 | 
| File Format | |
| ISBN | 0769525229 | 
| DOI | 10.1109/AICT-ICIW.2006.196 | 
| Language | English | 
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) | 
| Publisher Date | 2006-02-19 | 
| Publisher Place | French Caribbean | 
| Access Restriction | Subscribed | 
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) | 
| Subject Keyword | Pervasive computing Ubiquitous computing Context-aware services Immune system Computer vision Personal digital assistants Hospitals Protocols Context modeling Autonomous agents Immune system. Service composition and emergence Anytime/anywhere elearning Reinforcement learning collaborative mobile learning Agent-based system | 
| Content Type | Text | 
| Resource Type | Article | 
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