Energy-Efficient Task Assignment Based on Entropy Theory and Particle Swarm Optimization Algorithm for Wireless Sensor Networks

Network lifetime is one of important performance index for wireless sensor networks. It is essential that the tasks are assigned in the wireless sensor networks in order to complement this index. Therefore, a new energy-saving task assignment method is proposed. This method describes a cost function based on entropy theory according to the nodes status, such as computing resources, the residual energy and the number of neighbors. Meanwhile, particle swarm optimization algorithm is used to optimize dynamic task assignment. The tasks can be dynamic adjusted due to sensor network changing. The simulation results show that the execution time and energy consumption can be decreased and the lifetime of wireless sensor network is prolonged with the proposed method.