Efficient data handover and intelligent information assessment in software‐defined vehicular social networks

Abstract

Emerging trends in future Intelligent Transportation System allow vehicles to have on-board sensors and digital computers, which might help in real-time information exchange among neighbour vehicles. However, considering infected sensors, computer malfunctioning, and selfishness, legitimate vehicles might inject untrustworthy information into the network. In this situation, to find the credibility of disseminated information in less time delay is the key agenda. To provide a better solution and seamless interconnectivity among vehicles, the authors have proposed software-defined vehicular social networks (VSN). The proposed scheme takes advantage of social connections among vehicles, which are created and maintained over software-defined networking (SDN) cloud. The choice of using SDN cloud is due to its open flow nature, as the devices are more programmable and can be used to optimise the network operation. SDN based on these social connections is able to efficiently handover relevant data from truster to trustee vehicle. The closeness of the relationship between two vehicles in these VSN is modelled and assessed with TrustWalker algorithm by applying novel three-valued subjective logic operations. In the end, to validate the proposed scheme, packet loss and delay are considered as important network evaluation metrics. Performance analysis is done under different schemes and simulation results support the proposed scheme in terms of execution time.