A Workflow Scheduling Method for Cloudlet Management in Mobile Cloud

Cloudlet has emerged as a new paradigm to improve the ability to perform complex computations in mobile cloud computing. However, cloudlet suffers from the challenge of inefficient resource utilization as most of the times it operates below optimum resource utilization conditions. This results in waste of vital resources and increase in computation cost. So keeping in view this challenge, in this paper, a Workflow Scheduling Method (WSM) for cloudlet is proposed, which leverages Genetic Algorithm (GA) for efficient work flow tasks scheduling. Extensive experiments are performed to compare WSM with state of the art work flow task management method MCGA and Benchmark algorithm GA. Experimental evaluation shows that WSM outperforms both techniques and reduce the time cost of workflows and optimize the resource utilization of the cloudlet.