Matching game theoretical model for stable relay selection in a UAV-assisted internet of vehicles

Abstract This paper tackles the problem of selecting stable relays for Optimized Link State Routing protocol (OLSR) in urban Internet of Vehicles (IoV) in the presence of Unmanned Aerial Vehicles (UAVs). With the evolution of Internet of Things (IoT), IoV emerged from the conventional vehicular ad-hoc network to enable Vehicle to Everything (V2X) communication through different routing protocols. In OLSR protocol, Multi-Point Relays (MPRs) are selected based on their reachability and uniqueness to route information. However, urban environments are characterized by the rapid changes in topology due to the presence of intersections and traffic lights. Although clusters were proposed as a solution, selecting stable heads and MPRs are of significance, considering environment metrics to provide higher connectivity. As a solution to improve routing in IoV, a distributed Gale-Shapley matching game is proposed for stable clustering and MPR selection, utilizing nodes' quality of service (QoS). Nodes' QoS is calculated using Bayesian Belief function of stable connections utilizing environment metrics. For further enhancement in the network performance, UAVs are integrated in the network of vehicles. Conducted simulations show high percentage of stable heads and MPRs for the proposed model compared to benchmark protocols. In addition, the proposed model shows high performance in terms of packet delivery ratio, throughput and End-to-End delay, which are further improved by the presence of UAVs.