Evolution of cooperation in vehicular cloud assisted networks for ITS services: A hunt game-based approach

Abstract

Modern-day vehicles that are generally equipped with advanced sensors, devices, and communication technologies and sophisticated cloud computing facilities paved the way for vehicular cloud-assisted networks. It has the potential to effectively offer a broad range of on-demand services to help intelligent transportation systems sustain current traffic loads. The system can be fully functional only when the vehicles remain available and cooperate to form such a system and provide services. However, the behavior of the nodes is highly dependent on the neighborhood environment and the needs of the owner. Hence, nodes may bail out from the system at random. Therefore, the stimulation of cooperation becomes a research challenge. In this work, we analyzed the behavior of nodes by modeling the event of intelligent transportation service provisioning in a vehicular cloud-assisted network as a cooperative hunt game to find a sufficient condition under which cooperation could be evolved. Subsequently, an incentive-based cooperation scheme is proposed that guarantees optimal incentives to the nodes depending upon their roles and the amount of participation in the network activities. To evaluate the scheme, we have created a static vehicular cloud testbed that provides Intelligent Transportation services like optimal route information to vehicles. Evaluation results show that our scheme brings about conditions where obeying network protocols and serving faithfully to the system becomes the most suitable and stable strategy for nodes. We have also analyzed various network parameters such as end-to-end delay, packet delivery ratio, normalized acceptance rate, normalized delivery rate, etc., that show the improvement in network performance as compared to other strategies.