Direct acyclic graph-based ledger for internet of things: performance and security analysis

Li, Y., Cao, B., Peng, M., Long, Z., Zhang, L. , Feng, D. and Yu, J. (2020) Direct acyclic graph-based ledger for internet of things: performance and security analysis. IEEE/ACM Transactions on Networking, 28(4), pp. 1643-1656. (doi: 10.1109/TNET.2020.2991994)

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Abstract

Direct Acyclic Graph (DAG)-based ledger and the corresponding consensus algorithm has been identified as a promising technology for Internet of Things (IoT). Compared with Proof-of-Work (PoW) and Proof-of-Stake (PoS) that have been widely used in blockchain, the consensus mechanism designed on DAG structure (simply called as DAG consensus) can overcome some shortcomings such as high resource consumption, high transaction fee, low transaction throughput and long confirmation delay. However, the theoretic analysis on the DAG consensus is an untapped venue to be explored. To this end, based on one of the most typical DAG consensuses, Tangle, we investigate the impact of network load on the performance and security of the DAG-based ledger. Considering unsteady network load, we first propose a Markov chain model to capture the behavior of DAG consensus process under dynamic load conditions. The key performance metrics, i.e., cumulative weight and confirmation delay are analysed based on the proposed model. Then, we leverage a stochastic model to analyse the probability of a successful double-spending attack in different network load regimes. The results can provide an insightful understanding of DAG consensus process, e.g., how the network load affects the confirmation delay and the probability of a successful attack. Meanwhile, we also demonstrate the trade-off between security level and confirmation delay, which can act as a guidance for practical deployment of DAG-based ledgers.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Zhang, Dr Lei
Authors: Li, Y., Cao, B., Peng, M., Long, Z., Zhang, L., Feng, D., and Yu, J.
College/School:College of Science and Engineering > School of Engineering > Systems Power and Energy
Journal Name:IEEE/ACM Transactions on Networking
Publisher:IEEE
ISSN:1063-6692
ISSN (Online):1558-2566
Published Online:20 May 2020
Copyright Holders:Copyright © 2020 IEEE
First Published:First published in IEEE/ACM Transactions on Networking 28(4): 1643-1656
Publisher Policy:Reproduced in accordance with the publisher copyright policy

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
304481Resource Orchestration for Diverse Radio SystemsLei ZhangEngineering and Physical Sciences Research Council (EPSRC)EP/S02476X/1ENG - Systems Power & Energy