Clustering Routing Algorithm in Self-energized Wireless Sensor Networks

Abstract

Aiming at the existing clustering algorithms for self-energized wireless sensor network have neglected the actual environment that different geographic area has acquired different energy harvesting level, which resulting in less cluster heads, large-scale cluster region and network energy-imbalanced in lower energy harvesting areas. In this paper, we propose a novel clustering routing algorithm-CRAS (Clustering Routing Algorithm for Self-energized), which combines with the real energy harvesting scenario to improve the cluster-head election mechanism. Meanwhile, it adopts an adaptive inter-cluster communication mechanism, to sufficiently store and utilize the harvesting energy. Theoretical and simulation results manifest that CRAS algorithm can better keep the default cluster head proportion in the whole network, and it outperforms the two present algorithms in terms of the average residual energy and current available nodes number in the networks.