Chimp Optimization Algorithm Contribution Support To Increases Energy Efficiency In UWASN

Chimp Optimization Algorithm Contribution Support To Increases Energy Efficiency In UWASN | 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 Chimp Optimization Algorithm Contribution Support To Increases Energy Efficiency In UWASN A Kannappan, Nagesh Kolagani This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4166846/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 Underwater wireless Acoustic sensor network (UWASN) is employed to communicate between anchor nodes and the sink nodes. In this work, a novel Chimp optimization algorithm is deployed for underwater routing protocol communication, aiming to improve energy efficiency, packet delivery ratio, and throughput. In Chimp, the energy Optimization Algorithm solves the problems of propagation delay and improves battery life, network lifetime, and throughput. The proposed algorithm shows a better result in energy efficiency when compared to the existing buffalo algorithm, resulting in a Mean Delay of 79.17% and propagation delay of 74.35% than the existing counterpart. Especially compared to the buffalo algorithm, the Chimp algorithm has higher decision-making capacity and extended node range. The node range is set from 0 to 100, and the node performance is evaluated using MATLAB simulation software tools UWASN Buffalo Algorithm Chimp Algorithm Energy Efficiency Optimization Full Text Additional Declarations Competing interest reported. Existing Research paper Data validate is better combination and support to extended Sensor Battery lifetime. Existing paper They are compare Two Bio inspired Algorithm not detailed but Here comparing Algorithm very detailing Discuss 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. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4166846","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":297499137,"identity":"9073e8ba-aed4-4a4f-813a-219958fadbee","order_by":0,"name":"A Kannappan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+klEQVRIiWNgGAWjYBACgwNwJhsDwwcQxU5Ai2EDQgtj4wwQxUxAizGCycbYzAOiCWkxYz977MHPHXfkzdmPpT+2+bVNno+ZgfHDxxzcWmx48tINe888M9zZk3awObfvtmEbMwOz5MxteLQw5JhJ8LYdZtxwg72xObfnNiNQCxszLx4tZvxvzCT/th22B2ux7LltT1CLsUSOmTTQlsQNN9gONjP8uJ1IUIvhjDdm0rJnniVvOJOWOLO34XZyGzNjM16/GJzPMZN8u+OO7Ybjxww+/Phz23Z+e/PBDx/xaAEDxoYDUEYbhEtAPbIWhj+EFY+CUTAKRsHIAwCakVaC/isAswAAAABJRU5ErkJggg==","orcid":"","institution":"Saveetha School of Engineering, SIMATS","correspondingAuthor":true,"prefix":"","firstName":"A","middleName":"","lastName":"Kannappan","suffix":""},{"id":297499139,"identity":"604d5039-9a52-4a1c-93db-499f5567ceca","order_by":1,"name":"Nagesh Kolagani","email":"","orcid":"","institution":"Saveetha School of Engineering, SIMATS","correspondingAuthor":false,"prefix":"","firstName":"Nagesh","middleName":"","lastName":"Kolagani","suffix":""}],"badges":[],"createdAt":"2024-03-26 04:14:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4166846/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4166846/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":55816817,"identity":"20c2fee2-b1d9-4952-a0a2-44b083cab422","added_by":"auto","created_at":"2024-05-03 20:11:34","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":590735,"visible":true,"origin":"","legend":"","description":"","filename":"41.ChimpAlgorithmUWASN.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4166846/v1_covered_c83afe19-0847-400e-9e89-a191ccf9fc43.pdf"}],"financialInterests":"Competing interest reported. 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