Fuzzy intelligence based V2V routing protocol in Internet of Vehicles: a cross-layer approach

Internet of Vehicles (IoV), a vital component in intelligent transportation systems, supports diverse applications ranging from periodic safety message exchanges to on-demand multimedia streaming, gaming, and infotainment. Unicast routing is one of the primary techniques that support many such applications. Due to its highly dynamic nature and variable channel conditions, routing is extremely challenging in IoVs. Multiple contrasting metrics comprising cross-layer information need to be jointly examined to achieve an effective and reliable routing decision. In this paper, we propose a new unicast V2V routing protocol that consolidates and harmonizes the conflicting cross-layer and positional metrics such as distance, direction, link quality, link lifetime, available bandwidth, and queue information to select the most suitable next-hop nodes while forwarding packets. We combine these contrasting metrics using Fuzzy Logic to present a new intelligent routing protocol. Extensive simulation shows that our proposed protocol outperforms the standard existing routing techniques in terms of packet delivery ratio and average end-to-end delay across diverse vehicular environments.