Fuzzy Logic-Based Adaptive Clustering for Enhanced Stability and Energy Efficiency in FANETs

Fuzzy Logic-Based Adaptive Clustering for Enhanced Stability and Energy Efficiency in FANETs | 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 Fuzzy Logic-Based Adaptive Clustering for Enhanced Stability and Energy Efficiency in FANETs Mohamed Aissa, Badia Bouhdid, Mahmood Al Bahri, Muhammad Zakarya, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7026853/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Oct, 2025 Read the published version in Telecommunication Systems → Version 1 posted 16 You are reading this latest preprint version Abstract Flying Ad Hoc Networks (FANETs), formed by small drones operating in an ad hoc configuration, face significant hurdles in designing efficient routing protocols due to their three-dimensional movement, rapid topological shifts, high mobility, resource constraints, and sparse node distribution. This study models the clustering and cluster head (CH) selection challenge in FANETs as a constrained combinatorial optimization problem, recognized as NP-hard, requiring innovative and resilient solutions. We introduce ESOFCluster, a pioneering CH selection strategy that employs a fuzzy logic framework to manage the dynamic characteristics of FANETs. The framework utilizes four normalized parameters—residual energy, safe average distance, relative velocity, and link connectivity duration—to facilitate energy-efficient, stable, and flexible cluster formations. Through simulations in NS-3 with a realistic mobility model, the proposed approach named ESOFCluster is evaluated against LEACH, EMASS, and SOFCluster using FANET-specific performance indicators such as role change frequency, packet delivery success, cluster durability, and energy usage. The findings reveal that ESOFCluster outperforms its counterparts by improving network robustness, enhancing data transmission reliability, extending cluster persistence, and optimizing energy efficiency. These advancements establish ESOFCluster as a versatile and scalable clustering solution for FANETs, offering substantial potential for use in UAV swarms, disaster management, and critical missions where dependable and energy-conscious communication is vital. Adaptive Clustering Fuzzy Logic Systems Flying Ad Hoc Networks (FANETs) Energy Efficiency Network Stability Cluster Head Selection Dynamic Topology Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 06 Oct, 2025 Read the published version in Telecommunication Systems → Version 1 posted Editorial decision: Revision requested 24 Aug, 2025 Reviews received at journal 29 Jul, 2025 Reviews received at journal 24 Jul, 2025 Reviewers agreed at journal 23 Jul, 2025 Reviewers agreed at journal 23 Jul, 2025 Reviewers agreed at journal 23 Jul, 2025 Reviews received at journal 23 Jul, 2025 Reviews received at journal 18 Jul, 2025 Reviews received at journal 18 Jul, 2025 Reviewers agreed at journal 16 Jul, 2025 Reviewers agreed at journal 09 Jul, 2025 Reviewers agreed at journal 06 Jul, 2025 Reviewers invited by journal 06 Jul, 2025 Editor assigned by journal 02 Jul, 2025 Submission checks completed at journal 02 Jul, 2025 First submitted to journal 02 Jul, 2025 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. 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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-7026853","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":482697447,"identity":"420de951-3767-4c16-981f-cea2cee3e959","order_by":0,"name":"Mohamed Aissa","email":"","orcid":"","institution":"University of Nizwa","correspondingAuthor":false,"prefix":"","firstName":"Mohamed","middleName":"","lastName":"Aissa","suffix":""},{"id":482697451,"identity":"00120657-d83c-4e24-acb7-1cb9741dbac9","order_by":1,"name":"Badia Bouhdid","email":"","orcid":"","institution":"ESSPRIT School of 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