An Energy Efficient Clustering and Relay Selection Scheme for Cognitive Radio Sensor Networks

The new challenges are posed in the Cognitive Radio Sensor Network (CRSN) for designing techniques of topology maintenance. Satisfactory clustering may not be achieved with the previous spectrum-aware clustering methods because they rely on channel availability. In CRSNs, the energy-efficiency issue is caused due to the sensor nodes' constrained energies for data transmission. In clustered networks, the network activity collapsed due to the CHs' failure. The CHs with reliable selection should be performed in a network for energy balancing among CHs to prolong the network lifetime. An adaptive clustering method is proposed using the weighted clustering parameter. It considers the following parameters for CH selection: residual energy, queue length, spectrum availability and coverage of node. The proposed algorithm calculates a metric called Cluster Head Weight (CHW) for every node and selects the CHs based on this. After clustering and CH selection, the proposed algorithm incorporates an optimal relay selection algorithm based on Fuzzy Logic (FL) for quality relay node selection for inter and intra-cluster communications. The fuzzy system takes traffic index, link error rate and channel quality as inputs for relay selection. The proposed method provides improved performance by comparing with existing CRSN clustering methods based on routing overhead, end-to-end delay, network throughput, lifetime, and residual energy based on the analysis of obtained simulation results.