IPS: Incentive and Punishment Scheme for Omitting Selfishness in the Internet of Vehicles (Iov)

Abstract

Internet of Vehicles (IoV) is a new emerging concept and is an extended notion of Vehicular Ad-hoc networks (VANETs). In IoV the vehicles (nodes) are connected to the internet and able to transmit information. However, due to resources constraint nature of vehicles, they may not want to cooperate in order to save its own resources such as memory, energy, and buffer, etc. This behavior may lead to poor system performance. IoV needs an efficient solution to motivate the nodes in terms of cooperation to avoid selfish behavior. A novel mechanism Incentive and Punishment Scheme (IPS) has been proposed in this article where vehicles with higher weight and cooperation are elected as Heads during the election process. Vickrey, Clarke, and Groves (VCG) model has been used to scrutinize the weight of these heads. Vehicle participating in the election process can increase its incentives (reputation) by active participation (forwarding data). Vehicles with repeated selfish behavior are punished. The monitoring nodes monitor the performance of their neighbor nodes after the election process. A mathematical model and algorithms has been developed for the election, monitoring and incentive processes. The proposed approach has been simulated through VDTNSim environment to analyze the performance of the proposed IPS. The performance results demonstrate that the proposed schemes outperform the existing schemes in terms of packet delivery ratio, average delivery delay, average cost, and overhead.

Keywords

• Internet of vehicles
• smart objects
• VCG model
• selfish behavior
• incentive techniques