An Improved Sufferage Meta-Task Scheduling Algorithm in Grid Computing Systems

Scheduling tasks on heterogeneous resources distributed over a grid computing system is an NP-complete problem. Many scheduling algorithms have been developed aiming at reaching optimality. The Sufferage algorithm has shown a superlative performance over most meta-task scheduling algorithms regarding resources selection. However, providing a full power use of resources is still a challenge. In this paper, an improved heuristic algorithm of Sufferage is proposed. Its goal is to maximizing the resource utilization and minimizing the makespan. We adapt a new strategy for selecting proper resources. The main two criteria are the sufferage value and the minimum completion time. Our experimental results show that the proposed algorithm outperforms other algorithms in terms of flow time, utilization, and makespan.