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Workflow Scheduling Using Hybrid GA-PSO Algorithm in Cloud Computing

机译:云计算中混合GA-PSO算法的工作流调度

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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.
机译:云计算环境为客户端提供了几种按需服务和资源共享。使用工作流技术在云上管理业务流程,由于任务之间的依赖性,这代表了以高效方式使用资源的挑战之一。本文提出了一种混合GA-PSO算法,可以高效地将任务分配给资源。混合GA-PSO算法旨在减少构建时间和成本,并在云计算环境中的异构资源上平衡相关任务的负载。实验结果表明,与GA,PSO,HSGA,WSGA和MTCT算法相比,GA-PSO算法减少了工作流任务的总执行时间。此外,它降低了执行成本。此外,它还改进了工作流应用程序在可用资源上的负载平衡。最后,获得的结果还证明,与其他算法相比,该算法收敛速度更快,质量更高。

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