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Content Provider | IEEE Xplore Digital Library |
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Author | Yusoh, Z.I.M. Maolin Tang |
Copyright Year | 2012 |
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. |
Starting Page | 590 |
Ending Page | 597 |
File Size | 383191 |
Page Count | 8 |
File Format | |
ISBN | 9781467328920 |
ISSN | 21596190 |
DOI | 10.1109/CLOUD.2012.61 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2012-06-24 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Evolutionary Algorithm Cloud computing Placement Virtual machining Servers Resource management Software as a Service Optimization Genetic algorithms |
Content Type | Text |
Resource Type | Article |
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