A robust multi-objective optimization to workflow scheduling for dynamic grid

Grid computing infrastructure emerged as a next generation of high performance computing by providing availability of vast heterogenous resources. In the dynamic envirnment of grid, a schedling decision is still challenging area and it should consider reliability of reources while generating schedule in addition to other objectives. In this paper, we used evolutionary approach to obtain multiple trade-off soltions which minimizes makespan and cost along with the maximization of reliability under the deadline and budget constraints. We apply NSGA-II and ε - MOEA algorithms in order to explore solutions in the Pareto optimal front. Simulation analysis shows that multiple solutions obtained with ε -MOEA approach gives better convergence, uniform diversity in small computation time.