An entropy-based clustering algorithm for load balancing in WSN

Energy efficiency and traffic load balancing are the important factors for wireless sensor network (WSN) designer. To achieve the efficient energy consumption and well-distributed load balancing, the clustering techniques can be an efficient solution. Furthermore, the several applications like real-time surveillance require the guaranteed delay in order to satisfy their delay requirements. The guaranteed delay can be one of the critical design issues for these WSN applications as well. In this paper, we propose a novel clustering algorithm to solve the energy and delay issues in WSN. Our algorithm uses an entropy-based cluster cost function, which takes into account the traffic load and the traffic variation. The simulation results show that our algorithm has longer lifetime and lower delay than low-energy adaptive clustering hierarchy (LEACH) and hybrid energy-efficient distributed clustering (HEED).