Authors : B. Grace Jemimah; S. L. Chakradhar; E. Haswanth; Y. Tharun; G. Vani

Volume/Issue : Volume 11 - 2026, Issue 3 - March

Google Scholar : https://tinyurl.com/2xrnryxj

Scribd : https://tinyurl.com/3fmsbja3

DOI : https://doi.org/10.38124/ijisrt/26mar489

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Underwater wireless sensor networks are very important for collecting data in oceans, but these networks have serious problems like very low bandwidth, long signal delays, frequency issues and signal loss due to water. energy consumption is also much higher compared to normal wireless networks which causes batteries to die fast and reduces network coverage. most of the existing protocols focus on selecting next hop nodes or cluster heads but they ignore two main things - first is that sensor readings are often redundant and second is that most energy is used in transmitting data. this paper introduces CEAR which is basically a framework that reduces data using correlation-entropy selection and differential compression, and also optimizes routes by looking at remaining energy, signal loss and compressed data size. CEAR uses proper acoustic models, improved energy calculations for underwater and zone-based clustering to balance the load. simulations show that CEAR performs much better than protocols like LEACH, EECMR and EERBLC in terms of network lifetime, stable data delivery and energy efficiency. the results prove that combining compression with smart routing gives way better results for long term underwater missions.

Keywords : Underwater Sensor Networks; Energy-Aware Routing; Data Compression; Acoustic Communication.

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