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.

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Abstract:Cloud computing reformed the field of distributed systems and how businesses extend today. How to efficiently utilise the cloud computing resources to gain the maximum profit is one of the main research trends in the field, and the ultimate goal of cloud computing service providers. With the existence of virtualisation technology, running more than one virtual machines (VMs) on a single physical machine, brought a broad spectrum of benefits to service providers, researchers, etc. Therefore, this paper provides an analysis of the various VM load balancing algorithms. Further, a new VM load balancing algorithm has been proposed for an IaaS framework and implemented in a virtual machine environment of cloud-analyst to achieve better performance in terms of response and processing time.