Solving Task Scheduling Problem for Distributed Sensor Network with Discrete Particle Swarm Optimization

From the computation point of view, task scheduling for distributed sensor network is an NP-hard combinatorial optimization problem. The particle swarm optimization (PSO) has been proved to be a good optimization algorithm with outstanding global performance. However, PSO cannot be directly used in the combinatorial optimization problem mentioned above due to its continuity. In this paper, a heuristic discrete PSO (HDPSO) with a well-designed particle position code is proposed, in which effective fitness function based on approximate optimal waiting approach is adopted. Experiments show that the performance of the proposed algorithm is better than genetic algorithm.