A hybrid cost-effective genetic and firefly algorithm for workflow scheduling in cloud

Abstract

Cloud computing is developing as a new platform that gives high-quality information over the Internet at a very low cost. But still, it has numerous concerns that need to be focused. Workflow scheduling is the main serious concern in cloud computing. In this paper, we propose a Hybrid Cost-Effective Genetic and Firefly Algorithm (CEFA) for Workflow Scheduling in Cloud Computing. In the existing approach, the number of iteration was very large which increases the total execution cost and time which we will optimize in the proposed algorithm. The performance is estimated on scientific workflows and the results show that the proposed algorithm performs better than the existing algorithm. Three parameters are used to compare the performance of the existing and proposed algorithm; (1) execution time, (2) execution cost, and (3) termination delay.