Ant Colony Inspired Self-Healing for Resource Allocation in Service-Oriented Environment Considering Resource Breakdown

Authors:
Rong Zhou;Ren Wei;Gang Chen;Zhonghua Yang;Haifeng Shen;Jingbing Zhang;Ming Luo
Affiliations:
-;-;-;-;-;-;-
Venue:
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Year:
2008

Citing 3
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Abstract

The ant colony optimization (ACO) algorithm is a metaheuristic inspired from the behavior of foraging ants. Instead of exploring its ability in finding optimal solutions, the current study investigates another unique property – self-healing mechanism for resource allocation in a service-oriented environment where unexpected resource breakdown can occur. A system architecture is first proposed to detect, diagnose and react to disturbances. Then the performance of the ACO self-healing mechanism is tested and compared based on a modified benchmark problem. The experimental results show that the self-healing mechanism can promptly recover an obsolete schedule with high quality solutions.