TRETA-A Novel Heuristic Based Workflow Scheduling Algorithm in Cloud Environment

Abstract

Cloud computing is a new computing paradigm that lets users access services over the internet. Cloud provides scalable, on-demand resources and highly accessible. Cloud charges its customers for only the usage. Workflow applications are used in many business processing, scientific fields and in many other domains. Cloud has become one of the optimum solutions for executing workflows as for the computing power and the benefits it offers. Workflow scheduling can reduce the overall cost of execution and optimize resource utilization in the cloud for both the cloud consumer and the service provider. In this paper, We compare our novel algorithm Total Resource Execution Time Aware Scheduling Algorithm (TRETA) with existing heuristics which considers the total execution time of the computing resource as a factor for finding an optimal schedule. To the best of our knowledge none of the previous work has not considered the above metric for finding a better schedule. We compare the proposed algorithm with state-of-art heuristics First Come First (FCFS), Maximum Completion Time (MCT), Maximum Execution Time (MET), MaxMin, MinMin and Distributed Heterogeneous Earliest Finish Time (DHEFT) in the heterogeneous computing environment. The proposed algorithm is compared with other heuristics for the Makespan, Throughput and Degree of Imbalance. The experimentation is done for real workload traces of the CyberShake workflow of different task sizes generated from the Pegasus workflow management system using WorkflowSim. The proposed algorithm gives a better makespan and a better throughput like the other heuristics and results in a better Degree of Imbalance than the other heuristics.