A New Metaheuristic Approach to Task Assignment Problem in Distributed Systems

Task Assignment Problem (TAP) in distributed system is a key factor for obtaining better efficiency. TAP in a distributed system illustrates the appropriate allocation of tasks to the processor of each computer. In this problem the proposed methods up to now try to minimize communication cost. Since TAP is known as NP-Complete, many genetic approaches have been proposed to search optimal solutions from the entire solution space. Disregarding the techniques which can reduce the complexity of optimization, the existing approaches scan the entire solution space. On the other hand, this approach is time consuming in scheduling which is considered a shortcoming. Therefore, in this paper a hybrid metaheuristic algorithm has been proposed to overcome this shortcoming. Particle Swarm Optimization (PSO) has been applied as local search in the proposed metaheuristic approach in this paper. The proposed method has been compared to existing GA-based approach and one metaheuristic approach in which Tabu Search approach has been used as local search. The results demonstrated that the proposed approach outperform the above mentioned approaches in terms of Communication Cost.