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Stigmergic modeling for web service composition and adaptation

Citation

Moustafa, A and Zhang, M and Bai, Q, Stigmergic modeling for web service composition and adaptation, Proceedings of the 12th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2012): Lecture Notes in Computer Science, vol 7458, 3-7 September 2012, Kuching, Malaysia, pp. 324-334. ISBN 978-3-642-32694-3 (2012) [Refereed Conference Paper]


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Copyright 2012 Springer

DOI: doi:10.1007/978-3-642-32695-0_30

Abstract

As Web services become widespread, many complex applications require service composition to cope with high scalability and heterogeneity. Centralized Web service composition approaches are not sufficient as they always limit the scalability and stability of the systems. How to efficiently compose and adapt Web services under decentralized environments has become a critical issue, and important research question in Web service composition. In this paper, a stigmergic-based approach is proposed to model dynamic interactions among Web services, and handle some issues in service composition and adaptation. In the proposed approach, Web services and resources are considered as multiple agents. Stigmergic-based self-organization among agents are adopted to evolve and adapt Web service compositions. Experimental results indicate that by using this approach, service composition can be efficiently achieved, despite dealing with incomplete information and dynamic factors in decentralized environments.

Item Details

Item Type:Refereed Conference Paper
Keywords:web services, decentralized composition, dynamic adaptation
Research Division:Information and Computing Sciences
Research Group:Computer vision and multimedia computation
Research Field:Pattern recognition
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Application software packages
UTAS Author:Bai, Q (Dr Quan Bai)
ID Code:140692
Year Published:2012
Deposited By:Information and Communication Technology
Deposited On:2020-09-01
Last Modified:2020-11-09
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