Influence of Received Signal Strength on Prediction of Cluster Head and Number of Rounds

Research studies reveal the fact that clustering improves energy efficiency and network lifetime in wireless sensor networks (WSNs). In clustering, cluster head (CH) selection and rotation are the key techniques that have been adopted over a decade. CH selection based on the residual energy of the node, the distance of the node from the base station (BS), the degree of neighboring nodes (DNNs), the rate of recurrent communication of sensor nodes (RCSNs), etc., has been dealt in many articles. However, the impact of an obstacle on CH selection and number of rounds prediction is not addressed. Furthermore, the influence of an obstacle can be realized through the received signal strength indicator (RSSI). Hence, this proposal incorporates the RSSI as one of the parameters in CH selection. Fuzzy logic is employed to predict the CH. Then, based on the energy consumption of the CH, the number of rounds for the node to continue as the CH is predicted using a threshold. The proposal is simulated in MATLAB and implemented in hardware using Zigbee and Atmega controller. The results confirm the impact of received signal strength on CH selection and the number of rounds prediction. Furthermore, to overcome the shortfall of the existing first-order radio model, a linear regression-based energy prediction model is proposed. The proposed energy prediction model exhibits closeness with actual energy consumption which demonstrates its efficacy.