Intelligent Resource Allocation for Video Analytics in Blockchain-Enabled Internet of Autonomous Vehicles With Edge Computing

【Author】 Jiang, Xiantao; Yu, F. Richard; Song, Tian; Leung, Victor C. M.

【Source】IEEE INTERNET OF THINGS JOURNAL

【影响因子】10.238

【Abstract】Video surveillance in intelligent transportation systems (ITSs) is in the rapid growth stage, where video analytics is a potential technology to improve the safety of the Internet of Autonomous Vehicles (IoAV). However, massive video data transmission and computation-intensive video analytics bring an overwhelming burden for vehicular networks. Moreover, owing to the unstable network connection, the video data are not always reliable, which makes data sharing a lack of security and scalability in IoAV. In this work, we first propose a video analytics framework, where the multiaccess edge computing (MEC) and blockchain technologies are integrated into IoAV to optimize the transaction throughput of the blockchain system as well as reducing the latency of the MEC system. Furthermore, based on deep reinforcement learning, the joint optimization problem is modeled as a Markov decision process (MDP), and the asynchronous advantage actor-critic (A3C) algorithm is adopted to solve this problem. Simulation results demonstrate that our approach can fast converge and significantly improve the performance of blockchain-enabled IoAV with MEC.

【Keywords】Streaming media; Edge computing; Peer-to-peer computing; Optimization; Resource management; Throughput; Blockchain; deep reinforcement learning (DRL); Internet of Autonomous Vehicles (IoAV); multiaccess edge computing (MEC); video analytics

【发表时间】2022 AUG 15

【收录时间】2022-08-28

【文献类型】实验仿真

【主题类别】

区块链技术-协同技术-边缘计算