Blockchain-Based Trust Edge Knowledge Inference of Multi-Robot Systems for Collaborative Tasks

Jianan Li, Jun Wu*, Jianhua Li, Ali Kashif Bashir, Md Jalil Piran, Ashiq Anjum

*この研究の対応する著者

研究成果査読

1 被引用数 (Scopus)

抄録

Collaborative inference helps robots to complete large tasks with mutual collaboration in edge-assisted multi-robot systems. It is challenging to provide 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 multi-robot 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.

本文言語English
論文番号9502662
ページ(範囲)94-100
ページ数7
ジャーナルIEEE Communications Magazine
59
7
DOI
出版ステータスPublished - 2021 7
外部発表はい

ASJC Scopus subject areas

  • コンピュータ サイエンスの応用
  • コンピュータ ネットワークおよび通信
  • 電子工学および電気工学

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