Abstract

The Internet of Vehicles (IoV) is a decentralized network that enables data sharing between connected vehicles and vehicular ad hoc networks (VANETs). However, since different IoV applications have varied Quality-of-Service (QoS) requirements, creating an effective solution to cope with big data in IoV is challenging. Fog computing addresses the inherent flaw of centralized data processing in cloud computing by offloading computationally-intensive tasks to closely located fog nodes. Also, with an increasing number of vehicles under the IoV architecture, new challenges and requirements are emerging such as scalability, efficient resource usage, and secure communication. In this paper, we address the problems of load-balancing and secure communication in SDN-enabled and fog-based IoV networks. Our methodology (SaFIoV) efficiently distributes tasks in the fog-to-fog and vehicles-to-fog layers using reinforcement learning (RL) methods. Moreover, powered by Blockchain technology, our method provides secure communication. The result of our experimental study shows that SaFIoV can efficiently utilize the available resources while avoiding congestion and minimizing latency in the IoV network.

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