An Intelligent Framework for Stable Clustering in VANET Using Kohonen Network, Reinforcement Learning, and Multi-Criteria Optimization

An Intelligent Framework for Stable Clustering in VANET Using Kohonen Network, Reinforcement Learning, and Multi-Criteria Optimization | 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 An Intelligent Framework for Stable Clustering in VANET Using Kohonen Network, Reinforcement Learning, and Multi-Criteria Optimization Neda Sedighian, Abbas Karimi, Faraneh Zarafshan, Javad Mohammadzadeh This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7664257/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 Rapid vehicle movement and changes in overall vehicle density and distribution can make routing inefficient, cause delays, and create cluster instability while using VANETs (Vehicular Ad Hoc Networks). This paper intelligent frameworks focus on enhancing cluster stability and divides it into two stages: (1) the sophisticated weighted K-Medoid algorithm for signal strength and relative speed, node density, and movement direction-based initial clustering (2) dynamic weight adjustment self-organizing map (SOM) cluster head selection reinforcement learning (RL) optimization. NS-3 simulations (node density 50–150, speed 10–30 m/s) demonstrate the frameworks Adaptive RL border patrol outperformed SDPC, RL-neighbor selection, K-means, fuzzy logic with 9% SDPC, 15% K-means more PDR, improved end-to-end delay, cluster linger time, control traffic and greater RC. Adding RL improved adaptability and stabilization in high mobility fluctuating mover scenarios. Vehicular Ad Hoc Networks stable clustering Kohonen network reinforcement learning weighted K-Medoid multi-criteria optimization Full Text Additional Declarations No competing interests reported. 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-7664257","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":538676961,"identity":"cec20f9c-0bcc-4a57-b428-61ac1d2fc57e","order_by":0,"name":"Neda Sedighian","email":"","orcid":"","institution":"Islamic Azad University","correspondingAuthor":false,"prefix":"","firstName":"Neda","middleName":"","lastName":"Sedighian","suffix":""},{"id":538676962,"identity":"b7c207eb-4ce1-4ee0-804d-413f8b96c46f","order_by":1,"name":"Abbas 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