A QSQL-Based Service Collaboration Method for Automatic Service Composition, and Optimized Execution

A QSQL-Based Service Collaboration Method for Automatic Service Composition, and Optimized Execution

Kaijun Ren (National University of Defense Technology, China and Swinburne University of Technology, Australia), Jinjun Chen (Swinburne University of Technology, Australia), Nong Xiao (National University of Defense Technology, China) and Weimin Zhang (National University of Defense Technology, China)
DOI: 10.4018/978-1-60566-370-8.ch014
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Abstract

In scientific computing environments such as service grid environments, services are becoming basic collaboration components which can be used to construct a composition plan for scientists to resolve complex scientific problems. However, current service collaboration methods still suffer from low efficiency for automatically building composition plans because of the time-consuming ontology reasoning and incapability in effectively allocating resources to executing such plans. In this chapter, the authors present a QSQL-based collaboration method to support automatic service composition and optimized execution. With this method, for a given query, abstract composition plans can be created in an automatic, semantic, and efficient manner from QSQL (Quick Service Query List) which is dynamically built by previously processing semantic-related computing at service publication stage. Furthermore, concrete service execution instances can be dynamically bound to abstract service composition plans at runtime by comparing their different QoS(Quality of Service) values. Particularly, a concrete collaboration framework is proposed to support automatic service composition and execution. Totally, the authors’ proposed method will not only facilitate e-scientists quickly create composition plans from a large scale of service repository; but also make resource’s sharing more flexible. The final experiment has illustrated the effectiveness of their proposed method.

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