Performance evaluation of task scheduling using hybrid meta-heuristic in heterogeneous cloud environment

A. Saif, Faten and Derahman, Mohd Noor and Alwan, Ali Amer and Latip, Rohaya (2019) Performance evaluation of task scheduling using hybrid meta-heuristic in heterogeneous cloud environment. International Journal of Advanced Trends in Computer Science and Engineering, 8 (6). pp. 3249-3257. E-ISSN 2278-3091

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Abstract

Cloud computing is a ubiquitous platform that offers a wide range of online services to clients including but not limited to information and software over the Internet. It is an essential role of cloud computing to enable sharing of resources on-demand over the network including servers, applications, storage, services, and database to the end-users who are remotely connected to the network. Task scheduling is one of the significant function in the cloud computing environment which plays a vital role to sustain the performance of the system and improve its efficiency. Task scheduling is considered as an NP-complete problem in many contexts, however, the heterogeneity of resources in the cloud environment negatively influence on the job scheduling process. Furthermore, on the other side, the heuristic algorithms have satisfying performance but unable to achieve the desired level of efficiency for optimizing the scheduling in a cloud environment. Thus, this paper aims at evaluating the effectiveness of the hybrid meta-heuristic that incorporate genetic algorithm along with DE algorithm (GA-DE) in terms of make-span. In addition, the paper also intends to enhance the performance of the task scheduling in the heterogeneous cloud environment exploiting the scientific workflows (Cybershake, Montage, and Epigenomics). The proposed algorithm (GA-DE) has been compared against three heuristic algorithms, namely: HEFT-Upward Rank, HEFT – Downward Rank, and HEFT – Level Rank. The simulation results prove that the proposed algorithm (GA-DE) outperforms the other existing algorithms in all cases in terms of make-span.

Item Type:	Article (Journal)
Additional Information:	7094/77882
Uncontrolled Keywords:	Cloud computing, GA-DE, hybrid meta-heuristic, task scheduling.
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User:	DR. ALI A. ALWAN AL-JUBOORI
Date Deposited:	28 Jan 2020 11:12
Last Modified:	28 Jan 2020 11:12
URI:	http://irep.iium.edu.my/id/eprint/77882

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