Energy Consumption-Coverage Optimization for Node Deployment: Using Hybridized FOA-BAO Algorithm in Underwater Wireless Sensor Networks (UWSNs)

Energy Consumption-Coverage Optimization for Node Deployment: Using Hybridized FOA-BAO Algorithm in Underwater Wireless Sensor Networks (UWSNs) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Energy Consumption-Coverage Optimization for Node Deployment: Using Hybridized FOA-BAO Algorithm in Underwater Wireless Sensor Networks (UWSNs) Kadoke Marco, Sonia Goyal, Ranjit Kaur This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4529793/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Coverage and energy consumption are critical issues in underwater wireless sensor networks due to the unique challenges posed by the aquatic environment. This study introduces a hybrid fruit fly-bat optimization algorithm (FOA-BOA) for sensor node deployment in underwater wireless sensor networks (UWSNs). This technique leverages both fixed and mobile sensor nodes to enhance network connectivity and coverage. By developing a novel fitness function that incorporates coverage quality, connection cost, and network lifetime, the algorithm optimizes sensor node placement using modified bat and fruit fly optimization models. Probability detection and a hybrid FOA-BOA-based multipoint search are utilized to determine the optimal deployment configuration. Simulation results, compared with three existing algorithms, show that the proposed method significantly improves network coverage, reduces energy consumption, and extends network lifetime. These findings underscore the potential of this hybrid optimization technique to enhance UWSN performance in environmental monitoring applications. Sensor node Node deployment Coverage quality Energy consumption UWSNs Fruit fly Bat Full Text Additional Declarations Competing interest reported. Scholarship fulfilment under ICCR from 2022/2023 Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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