Blockchain-based Dependable Task Offloading and Resource Allocation for IIoT via Multi-Agent Deep Reinforcement Learning

被引:2
作者
Zhang, Peifeng [1 ,2 ,3 ,4 ]
Xu, Chi [1 ,2 ,3 ]
Xia, Changqing [1 ,2 ,3 ]
Jin, Xi [1 ,2 ,3 ]
机构
[1] Chinese Acad Sci, Shenyang Inst Automat, State Key Lab Robot, Shenyang, Peoples R China
[2] Chinese Acad Sci, Key Lab Networked Control Syst, Shenyang, Peoples R China
[3] Chinese Acad Sci, Inst Robot & Intelligent Mfg, Shenyang, Peoples R China
[4] Univ Chinese Acad Sci, Beijing, Peoples R China
来源
2023 IEEE 98TH VEHICULAR TECHNOLOGY CONFERENCE, VTC2023-FALL | 2023年
基金
中国国家自然科学基金;
关键词
IIoT; blockchain; task offloading; resource allocation; multi-agent deep reinforcement learning;
D O I
10.1109/VTC2023-Fall60731.2023.10333859
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Task offloading and resource allocation are fundamental and crucial for the edge computing-enhanced industrial Internet of things, where the security and credibility among massive heterogeneous devices are being challenged. This paper first proposes a novel blockchain consensus scheme named replicated and Byzantine fault tolerant, which can enhance the trust among nodes with the low communication cost. Then, with the objective of minimizing the task completion time, which includes credible verification, task offloading and transaction record, a joint task offloading and resource allocation problem with respect to blockchain verification ratio, offloading decision, communication and computing resources is formulated. Due to its non-convexity and the decentralized characteristic of blockchain, a multi-agent deep reinforcement learning algorithm with deterministic policy gradient is proposed to appropriate the optimal solution. Experiment results confirm the effectiveness of the proposed scheme in guaranteeing the timeliness and security.
引用
收藏
页数:6
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