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Trustworthy Service Selection and Composition

Trustworthy Service Selection and Composition TAA00004 ACM (Typeset by SPi, Manila, Philippines) 1 of 17 February 8, 2011 Trustworthy Service Selection and Composition CHUNG-WEI HANG and MUNINDAR P. SINGH, North Carolina State University We consider Service-Oriented Computing (SOC) environments. Such environments are populated with services that stand proxy for a variety of information resources. A fundamental challenge in SOC is to select and compose services, to support speci ed user needs directly or by providing additional services. Existing approaches for service selection either fail to capture the dynamic relationships between services or assume that the environment is fully observable. In practical situations, however, consumers are often not aware of how the services are implemented. We propose two distributed trust-aware service selection approaches: one based on Bayesian networks and the other on a beta-mixture model. We experimentally validate our approach through a simulation study. Our results show that both approaches accurately punish and reward services in terms of the qualities they offer, and further that the approaches are effective despite incomplete observations regarding the services under consideration. Categories and Subject Descriptors: H.3.5 [Information Storage and Retrieval]: Online Information Services ”Web-based services; I.2.11 [Computing Methodologies]: Distributed Arti cial Intelligence ” Intelligent agents General Terms: Algorithms, http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Autonomous and Adaptive Systems (TAAS) Association for Computing Machinery

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Publisher
Association for Computing Machinery
Copyright
Copyright © 2011 by ACM Inc.
ISSN
1556-4665
DOI
1921641.1921646
Publisher site
See Article on Publisher Site

Abstract

TAA00004 ACM (Typeset by SPi, Manila, Philippines) 1 of 17 February 8, 2011 Trustworthy Service Selection and Composition CHUNG-WEI HANG and MUNINDAR P. SINGH, North Carolina State University We consider Service-Oriented Computing (SOC) environments. Such environments are populated with services that stand proxy for a variety of information resources. A fundamental challenge in SOC is to select and compose services, to support speci ed user needs directly or by providing additional services. Existing approaches for service selection either fail to capture the dynamic relationships between services or assume that the environment is fully observable. In practical situations, however, consumers are often not aware of how the services are implemented. We propose two distributed trust-aware service selection approaches: one based on Bayesian networks and the other on a beta-mixture model. We experimentally validate our approach through a simulation study. Our results show that both approaches accurately punish and reward services in terms of the qualities they offer, and further that the approaches are effective despite incomplete observations regarding the services under consideration. Categories and Subject Descriptors: H.3.5 [Information Storage and Retrieval]: Online Information Services ”Web-based services; I.2.11 [Computing Methodologies]: Distributed Arti cial Intelligence ” Intelligent agents General Terms: Algorithms,

Journal

ACM Transactions on Autonomous and Adaptive Systems (TAAS)Association for Computing Machinery

Published: Feb 1, 2011

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