Task allocation for maximizing reliability of a distributed system using hybrid particle swarm optimization

In a distributed computing system, a number of program modules may need to be allocated to different processors such that the reliability of executing successfully these modules is maximized and the constraints with limited resources are satisfied. The problem of finding an optimal task allocation with maximum system reliability has been shown to be NP-hard; thus, existing approaches to finding exact solutions are limited to the use in problems of small size. This paper presents a hybrid particle swarm optimization (HPSO) algorithm for finding the near-optimal task allocation within reasonable time. The experimental results show that the HPSO is robust against different problem size, task interaction density, and network topology. The proposed method is also more effective and efficient than a genetic algorithm for the test-cases studied. The convergence and the worst-case characteristics of the HPSO are addressed using both theoretical and empirical analysis.