Dynamic grid scheduling algorithm based on self-adaptive Tabu Search

Abstract

In this paper, a self-adaptive algorithm based on Tabu Search (TS) is proposed to minimize the makespan, which is suitable to the grid dynamic characteristic. The process of scheduling is divided into partial scheduling, and last partial information is exploited to decide the next partial scheduling parameters set, which is self-adaptive to the stochastic environment. The algorithm was simulated in GridSim toolkit and the results demonstrated that the proposed algorithm improved performance compared to existing scheduling techniques.