Spider monkey optimisation based energy efficient clustering in heterogeneous underwater wireless sensor networks

Abstract

Multi-hop propagation is not viable in Underwater Wireless Sensor Network that uses acoustic signals. It causes more energy drainage of the network nodes due to longer delays in signal propagation. Also, UWSN is prone to dynamic topology changes due to node mobility caused by water current. It leads to transmission errors, link loss, collisions and congestion, if not well handled. A clustering approach based on spider monkey optimisation (SMO) is proposed here that addresses these issues. The proposed approach is found to enhance the average network lifetime of nodes by 0.01579 J and achieves a network gain of 1.35%. Further a significant reduction in average delay of messaging packets by 19.82% is achieved. The proposed approach is far more optimised as it reduces the average hops between sender and receiver by 20%.