MultiObjective Optimization to Workflow Grid Scheduling using Reference Point based Evolutionary Algorithm

Abstract

Grid facilitates global computing infrastructure for user to consume the services over the network. To optimize the workflow grid execution, a robust multi-objective scheduling algorithm is needed. In this paper, we considered three conflicting objectives like execution time (makespan), total cost and reliability. We propose a multi-objective scheduling algorithm, using R-NSGA-II approach based on evolutionary computing paradigm. Simulation results shows that the proposed algorithm generates multiple scheduling solutions near the Pareto optimal front with small computation overhead.