A cooperative coevolutionary algorithm for the composite SaaS placement problem in the cloud

Authors:
Zeratul Izzah Mohd Yusoh;Maolin Tang
Affiliations:
Queensland University Technology, Brisbane, QLD, Australia;Queensland University Technology, Brisbane, QLD, Australia
Venue:
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: theory and algorithms - Volume Part I
Year:
2010

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Abstract

Cloud computing has become a main medium for Software as a Service (SaaS) hosting as it can provide the scalability a SaaS requires. One of the challenges in hosting the SaaS is the placement process where the placement has to consider SaaS interactions between its components and SaaS interactions with its data components. A previous research has tackled this problem using a classical genetic algorithm (GA) approach. This paper proposes a cooperative coevolutionary algorithm (CCEA) approach. The CCEA has been implemented and evaluated and the result has shown that the CCEA has produced higher quality solutions compared to the GA.