A Modified Workflow Scheduling Algorithm for Cloud Computing Environment

Abstract

Cloud computing has gained many attentions. Workflow scheduling one of the most important issues in cloud computing. It involves mapping tasks onto cloud resources – Virtual machines (VMs), to improve scheduling performance. Because the existing heterogeneous earliest finish time (HEFT) algorithm is considered one of the best algorithm, so the work in this paper propose a new algorithm based on HEFT algorithm; called modified heterogeneous earliest finish time (M-HEFT); to reduce the tradeoff among make span, resource utilization, and load balance. The proposed M-HEFT consists of two phases; task prioritization and task-VM mapping. In Task prioritization phase, a priority will be provided to each task in directed acyclic graph (DAG) as in the original HEFT algorithm. According to task-VM phase, tasks allocate to resources according to length of tasks and the load of available VMs with considering load balance. To evaluate the performance of the proposed algorithm, a comparative study has been done among the proposed algorithm and three existed algorithms. The experimental results show that the proposed algorithm outperforms the other algorithms by minimizing make span by 29%, improve resource utilization by 53% and load balance by 18% in average