Volume 1, Issue 1, March 2018, Page: 24-30
An Efficient Algorithm for Workflow Scheduling in the Clouds Based on Differential Evolution Method
Toan Phan Thanh, Faculty of Technology Education, Hanoi National University of Education, Ha Noi, Viet Nam
Loc Nguyen The, Faculty of Information Technology, Hanoi National University of Education, Ha Noi, Viet Nam
Said Elnaffar, School of Engineering, Computer Science Department, American University of RAK, Ras al Khaimah, UAE
Received: Oct. 27, 2017;       Accepted: Dec. 4, 2017;       Published: Jan. 2, 2018
DOI: 10.11648/j.ajcst.20180101.14      View  1748      Downloads  138
The Cloud is a computing platform that provides on-demand access to a shared pool of configurable resources such as networks, servers, storage that can be rapidly provisioned and released with minimal management effort from clients. At its core, Cloud computing focuses on manimizing the effectiveness of the shared resources. Therefore, workflow scheduling is one of the challenges that the Cloud must tackle especially if a large number of tasks are executed on geographically distributed servers. The Cloud is comprised of computational and storage servers that aim to provision efficient access to remote and geographically distributed resources. To that end, many challenges, specifically workflow scheduling, are yet to be solved such. Despite it has been the focus of many researchers, a handful efficient solutions have been proposed for Cloud computing. In this work, we propose a novel algorithm for workflow scheduling that is derived from the Opposition-based Differential Evolution method, MODE. This algorithm not only ensures fast convergence but also averts getting trapped in local extrema. Our simulation experiments Cloud Sim show that MODE is superior to its predecessors. Moreover, the deviation of its solution from the optimal one is negligible.
Workflow Scheduling, Opposition-Based Differential Evolution, Cloud Computing, Differential Evolution
To cite this article
Toan Phan Thanh, Loc Nguyen The, Said Elnaffar, An Efficient Algorithm for Workflow Scheduling in the Clouds Based on Differential Evolution Method, American Journal of Computer Science and Technology. Vol. 1, No. 1, 2018, pp. 24-30. doi: 10.11648/j.ajcst.20180101.14
Copyright © 2018 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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