A Parallel Task Scheduling Algorithm for Scientific Workflows in Heterogeneous Cloud Environment

Abstract

Scheduling of the scientific workflows within the cloud and cloud dependent environment is challenging, because the data centers have heterogeneous nature resources. Scientific workflows are compute-intensive applications that need heterogeneous processing resources to realize high level of performance. Generally, the optimal scheduling of workflow tasks is a popular NP-complete type of problem. The authors have proposed a Depth Based Scheduling(DBS) for scientific  workflows and evaluated the same on using the Cybershake scientific workflow.  The main objective is to minimize the makespan of scientific workflows. Experimental results show that the proposed scheduling algorithm outperforms existing algorithms for cloud computing systems.