Journal of South China University of Technology(Natural Science Edition) ›› 2012, Vol. 40 ›› Issue (6): 126-131,158.

• Computer Science & Technology • Previous Articles     Next Articles

Dynamic KaaS Combination Strategy Based on Multi-Objective Ant Colony Optimization

Jia Rui-yu1  Wu Zhang-jun2  Zhang Yi-wen1,2   

  1. 1. School of Computer Science and Technology,Anhui University,Hefei 230039,Anhui,China; 2. School of Management,Hefei University of Technology,Hefei 230009,Anhui,China
  • Received:2011-12-11 Revised:2012-05-16 Online:2012-06-25 Published:2012-05-03
  • Contact: 贾瑞玉(1965-) ，女，副教授，主要从事智能软件、数据挖掘研究． E-mail:jiaruiyu267@ yahoo.com.cn
  • About author:贾瑞玉(1965-) ，女，副教授，主要从事智能软件、数据挖掘研究．
  • Supported by:

    国家"863”计划云制造主题项目( 2011AA040501) ; 国家自然科学基金资助项目( 70871033) ; 安徽省教育厅自然科学重点项目( KJ2011A006)

PDF

1057

Abstract:

In order to implement the knowledge sharing and integration in the form of Web services in cloud computing environments,a KaaS ( Knowledge as a Service) combination strategy based on multi-objective ant colony optimization is proposed. In this strategy,a dynamic KaaS combination model, which takes into consideration the dynamic characteristics of cloud computing environments and the QoS ( Quality of Service) rules of KaaS,is established from the viewpoint of knowledge service provider. Then,by redesigning the corresponding pheromone and heuristic information of the ant colony algorithm,the features of the problem are used to guide the searching process,and the multi-objective optimization is thus achieved. Finally,a simulation is conducted with real Web services on the cloud computing platform. The results indicate that,as compared with the strategies based on the genetic algorithm and the coevolution algorithm,the proposed strategy is more effective in terms of performance and solution quality.

Key words: cloud computing, multi-objective ant colony optimization, knowledge as a service

CLC Number: