Workflow Scheduling Using Hybrid GA-PSO Algorithm in Cloud Computing

• Published in: Wireless communications and mobile computing Vol. 2018; no. 2018; pp. 1 - 16
• Main Authors: Manasrah, Ahmad M., Ba Ali, Hanan
• Format: Journal Article
• Language: English
• Published: Cairo, Egypt Hindawi Publishing Corporation 01.01.2018; Hindawi; John Wiley & Sons, Inc
• Subjects: Algorithms; Business process management; Cloud computing; Genetic algorithms; Heuristic; Load; Optimization; Scheduling; Software services; Workflow software
• ISSN: 1530-8669; 1530-8677; 1530-8677
• DOI: 10.1155/2018/1934784

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.