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Clustering composite SaaS components in cloud computing using a grouping genetic algorithm

Mohd Yusoh, Zeratul Izzah & Tang, Maolin (2012) Clustering composite SaaS components in cloud computing using a grouping genetic algorithm. In IEEE Congress on Evolutionary Computation, IEEE Computer Society, International Convention Centre, Brisbane, QLD, pp. 1727-1734.

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Abstract

Recently, Software as a Service (SaaS) in Cloud computing, has become more and more significant among software users and providers. To offer a SaaS with flexible functions at a low cost, SaaS providers have focused on the decomposition of the SaaS functionalities, or known as composite SaaS. This approach has introduced new challenges in SaaS resource management in data centres. One of the challenges is managing the resources allocated to the composite SaaS. Due to the dynamic environment of a Cloud data centre, resources that have been initially allocated to SaaS components may be overloaded or wasted. As such, reconfiguration for the components’ placement is triggered to maintain the performance of the composite SaaS. However, existing approaches often ignore the communication or dependencies between SaaS components in their implementation. In a composite SaaS, it is important to include these elements, as they will directly affect the performance of the SaaS. This paper will propose a Grouping Genetic Algorithm (GGA) for multiple composite SaaS application component clustering in Cloud computing that will address this gap. To the best of our knowledge, this is the first attempt to handle multiple composite SaaS reconfiguration placement in a dynamic Cloud environment. The experimental results demonstrate the feasibility and the scalability of the GGA.

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ID Code: 51471
Item Type: Conference Paper
Keywords: Grouping Genetic Algorithms, Cloud Computing, Composite SaaS, Clustering
DOI: 10.1109/CEC.2012.6256562
ISBN: 9781467315081
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Artificial Intelligence and Image Processing not elsewhere classified (080199)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Current > Research Centres > Smart Services CRC
Copyright Owner: Copyright 2012 IEEE
Copyright Statement: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible
Deposited On: 09 Jul 2012 08:30
Last Modified: 05 Jan 2013 11:28

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