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

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.

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► An improved immune PSO is proposed for QoS-driven web service composition problem.
► New local best first strategy with same impacts on local and composite web service.
► A new learning and information accumulation mechanism is proposed for perturbation.
► Excellent performance especially for the size of the composite web service is large.