Distributed Resource Optimization With Blockchain Security for Immersive Digital Twin in IIoT
Jing Song, Ya Kang, Qingyang Song, Lei Guo, Abbas Jamalipour
Abstract
Virtual reality-embedded digital twin (VR-DT) service integrates digital twin with virtual reality to visualize the digital representation of real-world production, boosting the digital transformation of manufacturing industry in the Industrial Internet of Things (IIoT). Balanced against the advantages of the VR-DT service, its data-driven, computing-intensive, and security-sensitive features bring challenges to the current IIoT. Therefore, we propose a blockchain-based distributed resource allocation scheme to improve the average Quality of Service (QoS) of the VR-DT services with regard to service delay and transaction throughput. We formulate the joint optimization of channel assignment, subframe configuration, computing capacity allocation, and block size adjustment as a mixed-integer nonlinear programming problem. A fully decentralized multiagent compound-action actor–critic algorithm is developed to solve the QoS optimization problem. Simulation results demonstrate that our proposed scheme can efficiently improve the average QoS of the VR-DT services in a realizable way as compared to existing schemes.