An Improved Ant Algorithm for Grid Task Scheduling Strategy

Abstract

Task scheduling is an important factor that directly influences the performance and efficiency of the system. Grid resources are usually distributed in different geographic locations, belonging to different organizations and resources’ properties are vastly different, in order to complete efficiently, intelligently task scheduling, the choice of scheduling strategy is essential. This paper proposes an improved ant algorithm for grid task scheduling strategy, by introducing a new type pheromone and a new node redistribution selection rule. On the one hand, the algorithm can track performances of resources and tag it. On the other hand, add algorithm to deal with task scheduling unsuccessful situations that improve the algorithm's robustness and the successful probability of task allocation and reduce unnecessary overhead of system, shortening the total time to complete tasks. The data obtained from simulation experiment shows that use this algorithm to resolve schedule problem better than traditional ant algorithm.