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Composite SaaS placement and resource optimization in Cloud computing using evolutionary algorithms

Mohd Yusoh, Zeratul Izzah & Tang, Maolin (2012) Composite SaaS placement and resource optimization in Cloud computing using evolutionary algorithms. In Proceeding of the 2012 IEEE International Conference on Cloud Computing, IEEE Computer Society, Hyatt Regency Waikiki Resort and Spa, Honolulu, Hawaii, pp. 590-597.

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Abstract

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.

Impact and interest:

4 citations in Scopus
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ID Code: 51448
Item Type: Conference Paper
Keywords: Cloud computing, SaaS, Genetic Algorithm, Placement, Optimization
DOI: 10.1109/CLOUD.2012.61
ISBN: 978-1-4673-2892-0
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Neural Evolutionary and Fuzzy Computation (080108)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > DISTRIBUTED COMPUTING (080500) > Networking and Communications (080503)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
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Deposited On: 06 Jul 2012 08:17
Last Modified: 18 Aug 2012 18:18

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