Workflow task scheduling algorithm based on resource clustering in cloud computing environment

Abstract

Focusing on the characteristics of resource under large-scale,heterogeneous and dynamic environment in cloud computing,a workflow task scheduling algorithm based on resource fuzzy clustering was proposed.After quantizing and normalizing the resource characteristics,this algorithm integrated the theory of clustering to divide the resources based on the workflow task model and the resource model constructed in advance.The cluster with better synthetic performance was chosen firstly in scheduling stage.Therefore,it shortened the matching time between the task and the resource,and improved the scheduling performance.By comparing this algorithm with HEFT(Heterogeneous Earliest Finish Time) and DLS(Dynamic Level Scheduling),the experimental results show that the average SLR(Schedule Length Ratio) of this algorithm was smaller than that of HEFT by 3.4%,the DLS by 9.9%,and the average speedup of this algorithm was faster than that of HEFT by 5.9%,the DLS by 10.2% with the increase of tasks in a certain range of [0,100];when the resources were increased in a certain range of [0,100],the average SLR of this algorithm was smaller than that of HEFT by 3.6%,the DLS by 9.7%,and the average speedup of this algorithm was faster than that of HEFT by 4.5%,the DLS by 10.8%.The results indicate that the proposed algorithm realizes the reasonable division of resources,and it surpasses HEFT and DLS algorithms in makespan.