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Adaptive service composition in an ambient environment with a multi-agent system

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Abstract

The ambient intelligence consists of the integration of computer science technologies in the objects of the environment around us in order to create a smart one. Each object in the environment performs a different service as part of achieving a task. The adaptive Service composition is a context-aware system used in the situation where the user’s needs cannot be satisfied by a single service but by the combination of several ones. One of the main and principal characteristics of ambient environments is the adaptability to the context. The multi-agent systems with their characteristics of autonomy, proactivity, mobility and sociability are one of the most promising techniques of service composition and they became a major and significant paradigm for developping ambient systems. In this paper, we present a model of adaptive service composition in ambient environment based on multi-agent system named Multi Agent System for Adaptive Service Composition (MAS-ASC). To each object of the environment is associated an agent. The set of the agents coordinate their competences taking into account the context in order to perform an activity. MAS-ASC is based on the Contract Net Protocol in which the agents exchange their proposals in the form of call for proposal. It is implemented on Java Agent DEvelopment framework platform and has been tested to economize the consumption of energy in an intelligent lighting system example.

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Authors and Affiliations

  1. MISC Laboratory, University Constantine 2 Abdelhamid Mehri, Constantine, Algeria

    Aouatef Chaib & Allaoua Chaoui

  2. LIRE Laboratory, University Constantine 2 Abdelhamid Mehri, Constantine, Algeria

    Imane Boussebough

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  1. Aouatef Chaib
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  2. Imane Boussebough
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  3. Allaoua Chaoui
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Correspondence to Aouatef Chaib.

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Chaib, A., Boussebough, I. & Chaoui, A. Adaptive service composition in an ambient environment with a multi-agent system. J Ambient Intell Human Comput 9, 367–380 (2018). https://doi.org/10.1007/s12652-017-0510-8

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  • DOI: https://doi.org/10.1007/s12652-017-0510-8

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