SRBR: Anti-selfish Routing Based on Social Similarity and Reputation Using Fuzzy Logic

With the emergence of various applications in Intelligent Transportation Systems (ITS), the cooperative communication among vehicles has become increasingly important to provide transportation data services. However, vehicles with selfish behaviors rarely provide high-performance communication services to others, resulting in a low packet delivery ratio and a high end-to-end delay. It is extremely challenging to substantially alleviate the influence of selfish vehicles in vehicular networks, because of the network topology and unstable communication qualities. To address the above problems, the Social similarity and Reputation Based Routing (SRBR) is proposed, considering social relationships, vehicle behaviors, and transmission capacity. The social similarity can improve network performance by leveraging the social relationships of vehicles, while reputation mechanisms can effectively defend against selfish vehicles’ attacks. Additionally, to integrate the above two-dimensional metrics, fuzzy logic is employed. Furthermore, extensive results show SRBR outperforms other baseline schemes in terms of delivery ratio, average latency, and overhead ratio.