Optimized multi-superframe scheduling for clustered wireless sensor networks

Abstract

Since the power source for wireless sensor networks (WSN) is mainly from batteries, prolonging network life is an important requirement of the network. Hence, clustering algorithms are employed to decrease the number of packets in the network via data aggregation as well to reduce packet network collisions by adopting scheduled communication among nodes in a cluster. The composition of the superframe plays an important role in scheduling the communication among the nodes in the network as well as determining the application data rate of acquisition. The differential evolution (DE) algorithm is used to fulfill the objective, to maximize network life under different data acquisition rate. The data acquisition rate is dependent on the IEEE 802.15.4e superframe. In addition, the multi-superframe structure is utilized to enable nodes to conserve more energy. The proposed method provides a set of solutions, based on the constraints and goals.