Biogeography-based optimization of makespan and reliability in grid computing systems

The aim of this paper is to propose a scheduling method to consider reliability along with makespan in grid computing systems. The reliability of task execution is considered in the proposed method to increase the chance of running large-scale and computationally intensive workflows successfully. To handle situations in which a resource failure in a possible scheduling solution occurs, the proposed method finds a collection of scheduling solutions instead of only one solution to run the workflow. It leads to have chance to run an alternative scheduling solution that is not using the failed resource. To find the most optimized scheduling solutions, we exploit the lately developed biogeography-based optimization method with evaluation strategy and combine it with the operations like neighborhood search and crossover. Finally, the proposed method is compared with two successive scheduling methods. The results obtained from simulations show that gained improvement is significant especially in large workflows with large number of tasks.