SDN-Based Intelligent Multicast Protocol for Enhanced Vehicle-to-Vehicle Telescreen Using Hybrid Networks
Sarwar G. Syed I. Khan K. Ahmad S.
2025Institute of Electrical and Electronics Engineers Inc.
IEEE Transactions on Intelligent Transportation Systems
2025
This paper proposes SDN-MAOTRP, a multicriteria adaptive opportunistic multicast routing protocol that leverages Software-Defined Networking (SDN) and deep learning. It enables efficient Vehicle-to-Vehicle Telescreen (VVT) services, including delay-sensitive and real-time multimedia dissemination, and are critical components of Intelligent Transportation Systems (ITS). However, the deployment of VVT in ITS is hindered by challenges such as high mobility, frequent topology changes, packet loss, and latency, which degrade Quality of Service (QoS) and Quality of Experience (QoE). To address these challenges, SDN-MAOTRP incorporates an intelligent SDN controller which dynamically performs multicast routing decisions according to network conditions, user feedback, and historical data. In contrast to traditional multicast protocols that rely heavily on broadcasting - often resulting in network congestion and performance degradation - SDN-MAOTRP strategically decouples the control and data planes by utilizing LTE for control signaling and IEEE 802.11p for multimedia data transmission. Simulation results demonstrate that SDN-MAOTRP significantly improves both QoS and QoE, providing a scalable, efficient, and ITS-compliant solution for robust multimedia communication in dynamic vehicular environments.
ad hoc vehicular networks , deep neural networks , Intelligent transportation system , multi-media dissemination , software-defined networking
Text of the article Перейти на текст статьи
University of Azad Jammu and Kashmir, Department of Software Engineering, Muzaffarabad, 13100, Pakistan
Hankuk University of Foreign Studies, Department of Information and Communication Engineering, Yongin, 17035, South Korea
Nazarbayev University, School of Engineering and Digital Sciences, Department of Computer Science, Astana, 010000, Kazakhstan
Center of AI for Medical Research (CAIMI), Incheon, 22532, South Korea
University of Azad Jammu and Kashmir
Hankuk University of Foreign Studies
Nazarbayev University
Center of AI for Medical Research (CAIMI)
10 лет помогаем публиковать статьи Международный издатель
Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026