Grid task scheduling based on Chaotic Ant Colony Optimization Algorithm

Task scheduling and resource management is a key factor in the performance of the grid. Grid task scheduling needs to be achieved in several aspects, which include the performance aspects and economic aspects such as the optimal span, service quality, highest reliability, load balancing, to achieve maximum resource utilization. This paper presents a task scheduling strategy based on Chaotic Ant Colony Optimization Algorithm, using the randomness periodicity and regularity of chaotic motion to improve the quality of ant´s individuals, and the premature convergence of Ant Colony Optimization Algorithm and Genetic algorithm. In this paper, Matlab is used to make simulation experiments for the Chaotic Ant Colony Optimization algorithm and standard Genetic Algorithm, and the results show that the task scheduling algorithm is effective to decrease the running time.