An improved discrete immune optimization algorithm based on PSO for QoS-driven web service composition

  • Authors:

  • Xinchao Zhao;Boqian Song;Panyu Huang;Zichao Wen;Jialei Weng;Yi Fan

  • Affiliations:

  • School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China and State Key Lab. for Novel Software Technology, Nanjing University, Nanjing 210093, China;School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China;School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China;School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China;School of Computer, Beijing University of Posts and Telecommunications, Beijing 100876, China;School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China

  • Venue:
  • Applied Soft Computing
  • Year:
  • 2012

Quantified Score

Hi-index 0.00

Visualization

Abstract

An improved discrete immune optimization algorithm based on particle swarm optimization (IDIPSO) is proposed for Quality of Service (QoS)-driven web service composition with global QoS constraints. A series of effective strategies are presented for this problem, which include an improved local best first strategy based on mathematical analysis for candidate service selection, a perturbing global best strategy along the global best particle. The improved local best first strategy has equivalent effects on the local fitness of a candidate service and the fitness of a composite web service. Empirical comparisons with recently proposed algorithms on various scales of composite web service instances with global QoS constraints indicate that IDIPSO is highly competitive in terms of powerful searching capability, high stability and well trade-off between population diversity and selection pressure, especially when the size of the composite web service problem is large.