AIIV-Net: AI-Integrated Intent-Based Vehicular Networking Framework for Dynamic IoT Resource Orchestration in 6G-V2X Environments

AIIV-Net: AI-Integrated Intent-Based Vehicular Networking Framework for Dynamic IoT Resource Orchestration in 6G-V2X Environments | 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 AIIV-Net: AI-Integrated Intent-Based Vehicular Networking Framework for Dynamic IoT Resource Orchestration in 6G-V2X Environments Aitizaz Ali, Xu Ying, Kazim Raza Talpur, Bandeh Ali Talpur, Samar Raza Talpur, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7587601/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 10 You are reading this latest preprint version Abstract Internet of Things (IoT) and vehicle-to-vehicle (V2V) communication technologies are rapidly increasing, and an optimal resource allocation and network performance goal would be achieved using an intelligent, efficient, and scalable communication framework. The proposed intent-based V2V networking framework that includes AI in the paper will handle the flaws found in communication and the management of resources during V2V networks that are facilitated by the Internet of Things (IoT). The framework develops on the concepts of Intent-Based Networking (IBN) and Artificial Intelligence (AI), a new solution that addresses the issue of communication efficacy, resource management , and network optimization in highly dynamic heterogeneous systems. IBN enables the abstraction of the network coordinates and policies, and then resources can be allocated in a more dynamic and adaptable way depending on the various demands of V2V interactions. The help of AI as a part of this scheme makes it possible to involve intelligent decision-making, which allows the system to make predictions regarding network conditions and how to distribute and manage resources in a manner that provides a consistent communication channel between automated vehicles and IoT devices. The suggested framework has the capability of dynamically responding to traffic conditions, environmental conditions, and shifting communication loads, hence improving V2V communication performance within smart cities and connected surroundings. A large number of simulations and tests to evaluate its performance are carried out to demonstrate how the AI and IBN-included V2X communication system will optimize traffic flow and safety in ITS in urban areas. As compared to generic V2V communication frameworks, where latency and energy consumption are approximately 150 ms and 150 J to 100 J and 100 J, respectively, the proposed IBN-based V2X framework consumes considerably less energy (50 ms and 50 J) in terms of latency in the energy consumption. Artificial Intelligence (AI) Vehicle-to-Vehicle (V2V) Internet of Things (IoV) Intent-Based Networking (IBN) Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 06 May, 2026 Reviews received at journal 05 May, 2026 Reviewers agreed at journal 30 Apr, 2026 Reviewers agreed at journal 13 Oct, 2025 Reviews received at journal 22 Sep, 2025 Reviewers agreed at journal 17 Sep, 2025 Reviewers invited by journal 17 Sep, 2025 Editor assigned by journal 17 Sep, 2025 Submission checks completed at journal 12 Sep, 2025 First submitted to journal 11 Sep, 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. 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. 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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-7587601","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":518655347,"identity":"f07e0f80-396c-42cb-a703-58052c407abc","order_by":0,"name":"Aitizaz Ali","email":"","orcid":"","institution":"Qingdao University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Aitizaz","middleName":"","lastName":"Ali","suffix":""},{"id":518655348,"identity":"fcec8b87-b156-4802-a2e0-2683e8535455","order_by":1,"name":"Xu Ying","email":"","orcid":"","institution":"Qingdao University of Science and 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