Facilitating an ant colony algorithm for multi-objective data-intensive service provision

作者：

Highlights：

• This paper investigates bio-inspired algorithms applied in data intensive service provision.

• The paper focuses on the multi-objective optimization problems related to QoS and cost.

• The paper developed and facilitated ant colony systems to solve the Pareto optimal problems.

• This paper also compared ACO with genetic algorithms applied in the same problem.

• The paper demonstrated ACO had special features for further research in this area.

摘要

•This paper investigates bio-inspired algorithms applied in data intensive service provision.•The paper focuses on the multi-objective optimization problems related to QoS and cost.•The paper developed and facilitated ant colony systems to solve the Pareto optimal problems.•This paper also compared ACO with genetic algorithms applied in the same problem.•The paper demonstrated ACO had special features for further research in this area.

论文关键词：Ant colony system algorithm,Genetic algorithm,Multi-objective optimization,Data-intensive service composition,Cloud computing,Quality of service

论文评审过程：Received 13 May 2014, Revised 11 September 2014, Accepted 27 November 2014, Available online 12 December 2014.

论文官网地址：https://doi.org/10.1016/j.jcss.2014.11.017