Simulated Annealing Algorithm for Independent Tasks Assignment in Heterogeneous Computing Systems

Efficient tasks assignment is critical for achieving high performance in heterogeneous computing systems (HCS). The tasks assignment problem is NP-hard in general. In order to obtain better solutions, many assignment heuristics have been presented in the literature. Simulated Annealing (SA) algorithm is a powerful stochastic search method. It has been successfully used in many discrete optimization problems, such as TSP, JSP, and QAP, etc. After analyzing the impact of SA´s neighborhood on its performance, this paper defines two neighborhood structures first, then it presents a SA algorithm to tackle independent tasks assignment problem in HCS. The simulation results show that after using a suitable neighborhood system, SA algorithm is effective for independent tasks assignment problem in HCS.