WCSE 2017
ISBN: 978-981-11-3671-9 DOI: 10.18178/wcse.2017.06.100

Improved Grey Wolf Optimizer for Resource Constrained Web Service Management

Weimin Xiao, Haojiang Deng, Zhichuan Guo, Linlin Hu

Abstract— The Grey Wolf Optimizer (GWO) algorithm is a newly proposed swarm intelligence based algorithm. It is inspired by the social hierarchy and hunting behavior of grey wolves. However, in GWO different leader hierarchy of grey wolves are considered making contributions to the search results equally. This paper proposes an Improved Grey Wolf Optimizer (IGWO) algorithm for resource constrained web service management by adding weighted position factor to diverse hierarchy of grey wolves. IGWO is tested with standard dataset of PSPLIB to evaluate the ability of web service management in resource constrained system. The results prove that the IGWO algorithm is competitive compared to well-known meta-heuristics.

Index Terms— Improved Grey Wolf Optimizer, Resource Constrained, Web Service Management

Weimin Xiao, Haojiang Deng, Zhichuan Guo, Linlin Hu
National Network New Media Engineering Research Center, Institute of Acoustics, Chinese Academy of Sciences, CHINA
Weimin Xiao
University of Chinese Academy of Sciences, CHINA

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Cite: Weimin Xiao, Haojiang Deng, Zhichuan Guo, Linlin Hu, "Improved Grey Wolf Optimizer for Resource Constrained Web Service Management," Proceedings of 2017 the 7th International Workshop on Computer Science and Engineering, pp. 579-583, Beijing, 25-27 June, 2017.