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A Decentralized Self-Organizing Service Composition for Autonomic Entities

Published:01 February 2011Publication History
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Abstract

In service-oriented environments and distributed systems, service composition allows simple services to be dynamically combined into new, more complex services. Service composition techniques are usually designed as an extension to service discovery. Traditional techniques try to match a user’s requirements, often complex, with the available services. However, one-to-one matching is inefficient; it is preferable to meet the request from available services even when one of the basic services is not present. Separating composition and discovery has also led to inefficiency, especially in a highly dynamic environment. With the heterogeneity of networks, users, and applications having multiple sources, constructing service-specific overlays in large distributed networks is challenging. In this article, we propose a new service composition algorithm to deal with the problem of composing multiple autonomic elements to achieve system-wide goals. Using a self-organizing approach, autonomic entities are dynamically and seamlessly composed into service-specific overlay networks. The algorithm combines composition and service discovery into one step, thereby achieving more efficiency and less latency. The decentralized and self-organizing nature of the algorithm allows it to respond rapidly to system changes. Extensive simulation results validate the effectiveness of the approach when it is compared to other solutions.

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      • Published in

        cover image ACM Transactions on Autonomous and Adaptive Systems
        ACM Transactions on Autonomous and Adaptive Systems  Volume 6, Issue 1
        February 2011
        127 pages
        ISSN:1556-4665
        EISSN:1556-4703
        DOI:10.1145/1921641
        Issue’s Table of Contents

        Copyright © 2011 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 1 February 2011
        • Accepted: 1 July 2010
        • Revised: 1 March 2010
        • Received: 1 June 2009
        Published in taas Volume 6, Issue 1

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