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Wireless Communications and Mobile Computing
Volume 2018, Article ID 1934784, 16 pages
https://doi.org/10.1155/2018/1934784
Research Article

Workflow Scheduling Using Hybrid GA-PSO Algorithm in Cloud Computing

1Network and Information Security Department, Yarmouk University, Irbid 21163, Jordan
2Computer Sciences Department, Yarmouk University, Irbid 21163, Jordan

Correspondence should be addressed to Ahmad M. Manasrah; oj.ude.uy@a.damha

Received 27 September 2017; Accepted 11 December 2017; Published 8 January 2018

Academic Editor: B. B. Gupta

Copyright © 2018 Ahmad M. Manasrah and Hanan Ba Ali. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Cloud computing environment provides several on-demand services and resource sharing for clients. Business processes are managed using the workflow technology over the cloud, which represents one of the challenges in using the resources in an efficient manner due to the dependencies between the tasks. In this paper, a Hybrid GA-PSO algorithm is proposed to allocate tasks to the resources efficiently. The Hybrid GA-PSO algorithm aims to reduce the makespan and the cost and balance the load of the dependent tasks over the heterogonous resources in cloud computing environments. The experiment results show that the GA-PSO algorithm decreases the total execution time of the workflow tasks, in comparison with GA, PSO, HSGA, WSGA, and MTCT algorithms. Furthermore, it reduces the execution cost. In addition, it improves the load balancing of the workflow application over the available resources. Finally, the obtained results also proved that the proposed algorithm converges to optimal solutions faster and with higher quality compared to other algorithms.