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Fast and scalable distributed consensus over wireless large-scale Internet-of-Things network

Lee, Hojung; Seo, Hyowoon; Choi, Wan (2021-10-08)

 
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URL:
https://doi.org/10.1109/jiot.2021.3118928

Lee, Hojung
Seo, Hyowoon
Choi, Wan
Institute of Electrical and Electronics Engineers
08.10.2021

H. Lee, H. Seo and W. Choi, "Fast and Scalable Distributed Consensus Over Wireless Large-Scale Internet of Things Network," in IEEE Internet of Things Journal, vol. 9, no. 11, pp. 7916-7930, 1 June1, 2022, doi: 10.1109/JIOT.2021.3118928

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doi:https://doi.org/10.1109/jiot.2021.3118928
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Abstract

Due to the rapid paradigm shift in Internet of Things networks from wired and centralized to flexible wireless and decentralized networks, building effective and reliable distributed consensus mechanisms over wireless is becoming essential. Especially, since the performance of consensus over communication endpoints in a large-scale wireless network is limited by their communication capability, it requires a careful co-design of communication and consensus to attain a fast and scalable distributed wireless consensus mechanism with high resiliency against faulty nodes. Within this context, this article addresses such problem by designing two wireless consensus mechanisms that well-suit in large-scale wireless networks. On the one hand, as a reinterpretation of the conventional referendum consensus (RC) in a large-scale wireless network, gossip-broadcasting-based RC (GB-RC) is proposed. On the other hand, to overcome the scalability issue of the GB-RC, cooperative-broadcast-based electoral-college consensus (CB-EC) is proposed. By mathematically analyzing the performance of both of the consensus mechanisms, in terms of consensus latency and resiliency against the faulty nodes, we show that the GB-RC outperforms the conventional RC, while the CB-EC significantly reduces the consensus latency compromising the stochastic resiliency. We further evaluate their performance numerically to show their effectiveness and feasibility under realistic large-scale wireless environments.

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