Energy-efficient cluster head selection for cognitive radio sensor networks

Abstract

In this paper, we propose an Energy-Efficient Cluster Head Selection (ECHS) approach for Cognitive Radio Sensor Networks (CRSNs). ECHS achieves energy-efficient clustering while considering the dynamic channel access nature of CRSNs. ECHS is a distributed algorithm in which serving as a cluster head depends on two factors: the channel availability in the node's vicinity and the node's energy. To tackle the hot spot problem caused by the high traffic near the sink, ECHS forms many small clusters near the sink to share the forwarding load of the rest of the network. Dynamic channel assignment at the cluster heads is used to minimize the co-channel interference. Simulation results show that ECHS achieves a remarkable throughput increase while extending the network lifetime.