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

Li, J, Wu, J, Li, J, Bashir, AK, Piran, MJ and Anjum, A (2021) Blockchain-Based Trust Edge Knowledge Inference of Multi-Robot Systems for Collaborative Tasks. IEEE Communications Magazine, 59 (7). pp. 94-100. ISSN 0163-6804

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Official URL: https://ieeexplore.ieee.org/document/9502662

Abstract

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.

Item Type:	Article
Peer-reviewed:	Yes
Date Deposited:	15 Sep 2021 08:35
Publisher:	IEEE
Additional Information:	This is an Author Accepted Manuscript of a paper accepted for publication in IEEE Communications Magazine, published by and copyright IEEE.
Divisions:	Faculties > Science and Engineering Research Centres > Centre for Advanced Computational Science
Subject terms:	multi-robot system, Blockchain, Edge inference, knowledge graph, Networking & Telecommunications, 0805 Distributed Computing, 0906 Electrical and Electronic Engineering, 1005 Communications Technologies
URI:	https://e-space.mmu.ac.uk/id/eprint/628376
DOI:	https://doi.org/10.1109/MCOM.001.2000419
ISSN	0163-6804
e-ISSN	1558-1896

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