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SLA-based resource allocation for Software as a Service provider (SaaS) in cloud computing environments


Wu, L and Garg, SK and Buyya, R, SLA-based resource allocation for Software as a Service provider (SaaS) in cloud computing environments, Proceedings of the 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, 23-26 May 2011, California, USA, pp. 195-204. ISBN 978-0-7695-4395-6 (2011) [Refereed Conference Paper]

Copyright Statement

Copyright 2011 IEEE

DOI: doi:10.1109/CCGrid.2011.51


Cloud computing has been considered as a solution for solving enterprise application distribution and configuration challenges in the traditional software sales model. Migrating from traditional software to Cloud enables on-going revenue for software providers. However, in order to deliver hosted services to customers, SaaS companies have to either maintain their own hardware or rent it from infrastructure providers. This requirement means that SaaS providers will incur extra costs. In order to minimize the cost of resources, it is also important to satisfy a minimum service level to customers. Therefore, this paper proposes resource allocation algorithms for SaaS providers who want to minimize infrastructure cost and SLA violations. Our proposed algorithms are designed in a way to ensure that Saas providers are able to manage the dynamic change of customers, mapping customer requests to infrastructure level parameters and handling heterogeneity of Virtual Machines. We take into account the customersí Quality of Service parameters such as response time, and infrastructure level parameters such as service initiation time. This paper also presents an extensive evaluation study to analyze and demonstrate that our proposed algorithms minimize the SaaS providerís cost and the number of SLA violations in a dynamic resource sharing Cloud environment.

Item Details

Item Type:Refereed Conference Paper
Keywords:cloud computing, Service Level Agreement (SLA), resource allocation, scheduling, Software as a Service
Research Division:Information and Computing Sciences
Research Group:Distributed computing and systems software
Research Field:Distributed systems and algorithms
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Information systems, technologies and services not elsewhere classified
UTAS Author:Garg, SK (Dr Saurabh Garg)
ID Code:93876
Year Published:2011
Deposited By:Information and Communication Technology
Deposited On:2014-08-20
Last Modified:2014-12-08

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