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2012 IEEE Fifth International Conference on Cloud Computing
Composite SaaS Placement and Resource Optimization in Cloud Computing Using Evolutionary Algorithms
Honolulu, HI, USA USA
June 24-June 29
ISBN: 978-1-4673-2892-0
Software as a Service (SaaS) is gaining more and more attention from software users and providers recently. This has raised many new challenges to SaaS providers in providing better SaaSes that suit everyone needs at minimum costs. One of the emerging approaches in tackling this challenge is by delivering the SaaS as a composite SaaS. Delivering it in such an approach has a number of benefits, including flexible offering of the SaaS functions and decreased cost of subscription for users. However, this approach also introduces new problems for SaaS resource management in a Cloud data centre. We present the problem of composite SaaS resource management in Cloud data centre, specifically on its initial placement and resource optimization problems aiming at improving the SaaS performance based on its execution time as well as minimizing the resource usage. Our approach differs from existing literature because it addresses the problems resulting from composite SaaS characteristics, where we focus on the SaaS requirements, constraints and interdependencies. The problems are tackled using evolutionary algorithms. Experimental results demonstrate the efficiency and the scalability of the proposed algorithms.
Index Terms:
Servers,Optimization,Resource management,Cloud computing,Virtual machining,Genetic algorithms,Optimization,Software as a Service,Evolutionary Algorithm,Placement
Citation:
Zeratul Izzah Mohd Yusoh, Maolin Tang, "Composite SaaS Placement and Resource Optimization in Cloud Computing Using Evolutionary Algorithms," cloud, pp.590-597, 2012 IEEE Fifth International Conference on Cloud Computing, 2012
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