Performance Analysis for Blockchain Driven Wireless IoT Systems Based on Tempo-Spatial Model

Sun, Y. , Zhang, L. , Feng, G., Yang, B., Cao, B. and Imran, M. A. (2020) Performance Analysis for Blockchain Driven Wireless IoT Systems Based on Tempo-Spatial Model. In: CyberC 2019 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, Guilin, China, 17-19 Oct 2019, pp. 348-353. ISBN 9781728125428 (doi:10.1109/CyberC.2019.00066)

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Abstract

Blockchain has shown a great potential for Internet of Things (IoT) systems to establish trust and consensus mechanisms with no involvement of any third party. It has been not clear how the low complexity devices and the wireless communications among them can pose constraints on the blockchain enabled IoT systems. In this paper, we establish a fundamental analysis model to underpin the blockchain enabled IoT system. By considering spatio-temporal domain Poisson distribution, i.e., node geographical distribution and transaction arrival rate in time domain are both modeled as Poisson point process (PPP), we first derive the distribution of signal-to-interference-plus-noise ratio (SINR), blockchain transaction successful rate as well as overall throughput. Then, based on the analytical model, we design an optimal full function node deployment for blockchain system to achieve the maximum transaction throughput with the minimum full function node density. Numerical results validate the accuracy of our theoretical analysis and evaluate the relationship between blockchain full function node deployment and the density of IoT nodes.

Item Type:Conference Proceedings
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Yang, Mr Bowen and Zhang, Dr Lei and Imran, Professor Muhammad and Sun, Dr Yao and Feng, Professor Gang
Authors: Sun, Y., Zhang, L., Feng, G., Yang, B., Cao, B., and Imran, M. A.
College/School:College of Science and Engineering > School of Engineering
College of Science and Engineering > School of Engineering > Systems Power and Energy
ISBN:9781728125428
Copyright Holders:Copyright © 2019 IEEE
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher
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