Wireless distributed consensus for connected autonomous systems

Xu, H. , Fan, Y., Li, W. and Zhang, L. (2023) Wireless distributed consensus for connected autonomous systems. IEEE Internet of Things Journal, 10(9), pp. 7786-7799. (doi: 10.1109/JIOT.2022.3229746)

Abstract

Connected critical autonomous systems (C-CAS) are envisioned to significantly change our life and work styles through emerging vertical applications such as autonomous vehicles and cooperative robots. However, as the scale of the connected nodes continues to grow, their heterogeneity and cyber-security threats are more eminent, and conventional centralized communications and decision-making methodology are reaching their limit. This paper is the first exploration of a trustworthy and fault-tolerant framework for C-CAS for achieving hyper-reliable global decision-making in a trustless environment, where the connected sensors/nodes are less reliable due to either communication failure or local decision error (e.g., by sensing algorithm/AI, etc.). The proposed framework is based on two iconic distributed consensus (DC) mechanisms, practical Byzantine fault tolerance (PBFT) and Raft, under the proposed PICA (Perception-Initiative-Consensus-Action) protocol with wireless connections among the nodes. We first analytically derived consensus reliability in six different system models. The other fundamental performance metrics such as the consensus throughput and latency, node scalability and reliability gain are also analytically derived. These analytical results provide basic design guidelines for wireless Distributed Consensus (WDC) usage in the C-CAS systems. The results show that WDC significantly improves overall system reliability with the increasing number of participating nodes.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Fan, Ms Yixuan and Zhang, Professor Lei and Xu, Mr Hao
• Authors: Xu, H., Fan, Y., Li, W., and Zhang, L.
• College/School: College of Science and Engineering > School of Engineering; College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity; College of Science and Engineering > School of Engineering > Systems Power and Energy
• Journal Name: IEEE Internet of Things Journal
• Publisher: IEEE
• ISSN: 2327-4662
• ISSN (Online): 2327-4662
• Published Online: 16 December 2022
• Copyright Holders: Copyright © 2022 IEEE
• First Published: First published in IEEE Internet of Things Journal 10(9): 7786-7799
• Publisher Policy: Reproduced in accordance with the publisher copyright policy