Task duplication-based workflow scheduling for heterogeneous cloud environment

Workflow scheduling is a well-known NP-complete problem. As per the nature of the workflow scheduling for cloud computing environment researchers are dedicated to find out the optimal or near optimal solution based on different heuristics. Another key issue in the recent years is handling workflow in heterogeneous cloud system that is paying significant consideration of the research community. In this paper, we propose a task duplication-based workflow scheduling algorithm for heterogeneous cloud environment which is centered on task duplication realization. The proposed algorithm has two phases. The first phase computes the priority of all the tasks and second phase goes through the scheduling with task duplication by calculating data arrival time from one task to another task. Proposed algorithm aims to minimize workflow execution time and to maximize the resource utilization. The performance evaluation of the proposed algorithm is done on benchmark scientific workflow applications with different task-cloud heterogeneity. Comparisons of the simulated results with the some existing workflow scheduling algorithms noticeably show that the proposed algorithm outpaces in terms of makespan and average cloud utilization.