Abstract
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.