Edge Computing for Video Analytics in the Internet of Vehicles with Blockchain

In intelligent transportation systems (ITS), video analytics is a potential technology to enhance the safety of the Internet of Vehicles (IoV). However, massive video data transmission and computation-intensive video analytics bring an overwhelming burden for IoV. Furthermore, due to the unstable network connection, the video data are not always reliable, which makes data sharing lack of security and scalability in IoV. In this paper, for video analytics applications, the multi-access edge computing (MEC) and blockchain technologies are integrated into IoV to optimize the transaction throughput as well as reducing the latency of the MEC system. Furthermore, the joint optimization problem is formulated as a Markov decision process (MDP), and the asynchronous advantage actor-critic (A3C) algorithm is adopted to solve this problem. Simulation results show that the proposed approach can fast converge and signifcantly improve the performance of blockchain-enabled IoV with MEC.