Efficient population diversity handling genetic algorithm for qos-aware web services selection

  • Authors:

  • Chengwen Zhang;Sen Su;Junliang Chen

  • Affiliations:

  • State Key Lab of Networking and Switching Technology, Beijing University of Posts & Telecommunications(BUPT), Beijing, China;State Key Lab of Networking and Switching Technology, Beijing University of Posts & Telecommunications(BUPT), Beijing, China;State Key Lab of Networking and Switching Technology, Beijing University of Posts & Telecommunications(BUPT), Beijing, China

  • Venue:
  • ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part IV
  • Year:
  • 2006

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Abstract

To maximize user satisfaction during composition of web services, a genetic algorithm with population diversity handling is presented for Quality of Service(QoS)-aware web services selection. In this algorithm, the fitness function, the selection mechanism of the population as well as the competition mechanism of the population are represented. The population diversity and population fitness are used as the primary criteria of the population evolution. By competing between the current population and the historical optimal population, the whole population evolution can be done on the basis of the whole population evolution principle of the biologic genetic theory. Prematurity is overcome effectively. Experiments on QoS-aware web services selection show that the genetic algorithm with population diversity handling can get more excellent composite service plan than the standard genetic algorithm.