IEEE COmmag- Jun wu e.pdf (4.86 MB)
Blockchain-Based Trust Edge Knowledge Inference of Multi-Robot Systems for Collaborative Tasks
journal contributionposted on 2021-09-24, 14:26 authored by Jianan Li, Jun Wu, Jianhua Li, Ali Kashif Bashir, Md Jalil Piran, Ashiq Anjum
The collaborative inference helps robots to complete large tasks with mutual collaboration in edge-assisted multirobot systems. It is challenging to provide the trusted edge collaborative inference in the presence of malicious nodes. In this article, we propose a blockchain-based collaborative edge knowledge inference (BCEI) framework for edge-assisted multirobot systems. First, we formulate the inference process at the edge as the collaborative knowledge graph construction and sharing model. Second, to guarantee the trust of knowledge sharing, an efficient knowledge-based blockchain consensus method is presented. Finally, we conduct a case study on the emergency rescue application to evaluate the proposed framework. The experiment results demonstrate the efficiency of the proposed framework in terms of latency and accuracy.
CitationBlockchain-Based Trust Edge Knowledge Inference of Multi-Robot Systems for Collaborative Tasks. IEEE Communications Magazine, 59 (7). pp. 94-100.
Author affiliationSchool of Informatics
- AM (Accepted Manuscript)