Particle Swarm Optimization with Skyline Operator for Fast Cloud-based Web Service Composition

  • Authors:

  • Shangguang Wang;Qibo Sun;Hua Zou;Fangchun Yang

  • Affiliations:

  • State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China 100876;State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China 100876;State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China 100876;State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China 100876

  • Venue:
  • Mobile Networks and Applications
  • Year:
  • 2013

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Abstract

Quality of Services play an increasingly important role during the procedure of Cloud-based web service composition for seamless and dynamic integration of business applications. However, as Cloud-based web services (CWSs) proliferate, it becomes difficult to facilitate service composition quickly in Cloud computing environment. In this paper, based on the notion of Skyline, we propose a fast CWS composition approach. This approach adopts Skyline operator to prune redundant CWS candidates and then employs Particle Swarm Optimization to select CWS from amount of candidates for composing single service into a more powerful composite service. Based on a real dataset, we conduct an experiment to evaluate our proposed approach. Experimental results show that our proposed approach is effective and efficient for CWS composition.