N Sasikaladevi
School of Computing, SASTRA University

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RETRACTED: Minimum makespan task scheduling algorithm in cloud computing N Sasikaladevi
International Journal of Advances in Intelligent Informatics Vol 2, No 3 (2016): November 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v2i3.59

Abstract

RETRACTEDFollowing a rigorous, carefully concerns and considered review of the article published in International Journal of Advances in Intelligent Informatics to article entitled “Minimum makespan task scheduling algorithm in cloud computing” Vol 2, No 3, pp. 123-130, November 2016, DOI: http://dx.doi.org/10.26555/ijain.v2i3.59.This paper has been found to be in violation of the International Journal of Advances in Intelligent Informatics Publication principles and has been retracted.The article contained redundant material, the editor investigated and found that the paper published in International Journal of Grid and Distributed Computing, Vol. 9, No. 11, pp. 61-70, 2016, DOI: http://dx.doi.org/10.14257/ijgdc.2016.9.11.05.The document and its content has been removed from International Journal of Advances in Intelligent Informatics, and reasonable effort should be made to remove all references to this article.
SLA based cloud service composition using genetic algorithm N Sasikaladevi
International Journal of Advances in Intelligent Informatics Vol 2, No 2 (2016): July 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v2i2.58

Abstract

Cloud computing tends to provide high quality on-demand services to the users. Numerous services are evolving today. Functionally similar services are having different non-functional properties such as reliability, availability, accessibility, response time and cost. A single service is inadequate for constructing the business process. Such business process is modeled as composite service. Composite service consists of several atomic services connected by workflow patterns. Selecting services for service composition with the constraints specified in Service Level Agreement is the NP-hard problem. Such a cloud service composition problem is modeled in this paper. Genetic based cloud service composition algorithm (GCSC) is proposed. Proposed algorithm is compared with the existing genetic based cloud service composition algorithm based on average utility rate and convergence time. It is proved that the proposed algorithm provides better performance as compared to the existing cloud service composition algorithm.