EFFICIENCY ENERGY BALANCED UNEVEN NODE CLUSTERING LAYER IN UNDERWATER ACOUSTIC SENSOR NETWORK

Abstract

Underwater Acoustic Sensor Networks (UASNs) are commonly utilised for underwater data collecting and under water pollution identification. A UASN is made up of battery-powered acoustic sensors. Replacement of these batteries is challenging due to the challenging underwater conditions where UASNs are employed. One way to address this issue is to extend the battery capacity of UASNs by lowering its node energy usage (increasing energy efficiency). The EEBUCL algorithm, which increases the energy efficiency of acoustic sensors, is proposed in this work. The EEBUCL method creates UASNs composed of uneven layering dependent on node depth, addressing the "hot spot" problem by establishing of varied clusters sizes inside the particular layer. The EEBUCL algorithm successfully balances node energy in acoustic sensor nodes, extending lifetime of the network, according to simulation findings.