Cloud Provisioning for Workfow Application with Deadline using Discrete PSO

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Publication Details

Author list: Netjinda, N.;Sirinaovakul, B.;Achalakul, T.

Publication year: 2013

Journal: ECTI Transactions on Computer and Information Technology (2286-9131)

Volume number: 7

Issue number: 1

Start page: 43

End page: 51

ISSN: 2286-9131

Abstract

The need of cloud consumers to optimize all op- tions offered by cloud provider has been rapidly arisen during the recent years. The consideration involves the appropriate number of VMs must be purchased along with the allocation of supporting resources. Moreover, commercial clouds may have many differ- ent purchasing options. Finding optimal provision- ing solutions is thus an NP-hard problem. Currently, there are many research works discussing the cloud provisioning cost optimization. However, most of the works mainly concerned with task scheduling. In this paper, we proposed a new framework where number of purchased instance, instance type, purchasing op- tions, and task scheduling are considered within an optimization process. The Particle Swarm Optimiza- tion (PSO) technique is used to find the optimal so- lution. The initial results show a promising perfor- mance in both the perspectives of the total cost and fitness convergence. The designed system provides the solutions of purchasing options with optimum budget for any specified workflow-based application based on the required performance.

Keywords

Cloud Computing, Cloud Provisioning, Cost Optimization, Workflow Application, Deadline Constraint, Particle Swarm Optimization