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QoS-aware and multi-granularity service composition

Zaiwen Feng (), Rong Peng (), Raymond K. Wong (), Keqing He (), Jian Wang (), Songlin Hu () and Bing Li ()
Additional contact information
Zaiwen Feng: Wuhan University
Rong Peng: Wuhan University
Raymond K. Wong: University of New South Wales
Keqing He: Wuhan University
Jian Wang: Wuhan University
Songlin Hu: Chinese Academy of Sciences
Bing Li: Wuhan University

Information Systems Frontiers, 2013, vol. 15, issue 4, No 4, 553-567

Abstract: Abstract Composition of Web services can be very complex, and usually involves multiple atomic services and varieties of message exchange patterns. Worst still, with the increasing amount of available services with varying granularity and quality, selecting the best combination of services becomes very challenging. This paper addresses the issues on multi-granularity service composition with awareness of the service quality. In particular, we consider how a new service composition plan is produced, while preserving its original observable behaviors of a service that are shown to the service user, by substituting the service with another service or a set of services of finer or coarser grain. The new plan aims to have services of better quality (if the corresponding underlying services are available). To achieve this, we firstly define a behavioral signature model to capture observable behaviors of services. We then present that two service composition plans are choreography equivalent if they comply with the same behavioral signature model. We then propose a behavioral extracting algorithm to obtain the behavioral signature model from a service composition plan. We also present a method to determine choreography equivalence. Finally we briefly describe our prototype implementation that captures all these proposed algorithms.

Keywords: Service composition; Automatic; Behavioral compliance; Granularity; QoS (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s10796-012-9378-5

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