Loading [MathJax]/extensions/MathZoom.js
A Review of Research on Blockchain Consensus Mechanisms and Algorithms | IEEE Conference Publication | IEEE Xplore

A Review of Research on Blockchain Consensus Mechanisms and Algorithms


Abstract:

Blockchain technology is a distributed ledger technology whose core mechanism is the consensus mechanism. Consensus mechanism refers to the method of reaching agreement t...Show More

Abstract:

Blockchain technology is a distributed ledger technology whose core mechanism is the consensus mechanism. Consensus mechanism refers to the method of reaching agreement through collaboration and competition among participants in a distributed network. And the algorithm is the specific steps and rules to realize the consensus mechanism. This paper reviews and studies the blockchain consensus mechanism and algorithm. It begins by introducing the development background and application scenarios of blockchain technology. Blockchain technology has gained attention due to the rise of digital currencies and has been widely used in industries such as finance and IoT. Next, we elaborate on some common blockchain consensus mechanisms. Currently, there are several consensus mechanisms, including Proof of Work, Proof of Stake, and Delegated Proof of Stake. Each method has unique characteristics, so it is crucial to choose the most suitable one based on the usage environment. Next, the research progress of blockchain consensus algorithms is discussed. Along with the rapid progress of blockchain technology, numerous consensus algorithms have been introduced and practically utilized. These algorithms are able to ensure data consistency and security in distributed networks. This paper discusses the challenges and future development direction of blockchain consensus mechanisms and algorithms.
Date of Conference: 21-23 November 2024
Date Added to IEEE Xplore: 17 December 2024
ISBN Information:
Electronic ISSN: 2189-8723
Conference Location: Okinawa, Japan
References is not available for this document.

I. Introduction

Since 2008, when Satoshi Nakamoto wrote ‘Bitcoin: A Peer-to-Peer Electronic Cash System’, blockchain has increasingly become the focus of computer science research [1], from the release of bitcoin in 2008 to the release of ethereum in 2013 marking the blockchain’s entry from 1.0 to 2.0, with the continuous progress of the research, the sidechain technology rise, the proposal of sharding technology, and the implementation of cross-chain interoperability also mean that blockchain enters the 3.0 era, and with the hot momentum of the meta-universe, blockchain also enters the peak of development. As a disruptive technology, blockchain 3.0 has already sparked extensive academic and commercial interest worldwide in recent years due to its unique features of decentralization, traceability, tamper-proofing, and privacy protection. First, the research on Blockchain 3.0 has great academic value, covering many key innovations, such as sharding and sidechain technology, privacy protection, and cross-chain interoperability, which provides scholars with a broad and profound field of research that can promote the common progress of multiple disciplinary fields, such as computer science, cryptography, and distributed systems. Secondly, at the commercial level, blockchain 3.0 can be widely used in the fields of Internet of Things (IoT), healthcare, agriculture, etc., realizing many enterprise-level applications and solving real-life problems, which is crucial for realizing the digital transformation of enterprises and improving competitiveness in the industry. As a distributed and decentralized digital ledger, its internal consensus mechanism has become an important part.This paper conducts a statistical analysis and comprehensive overview of consensus algorithms, comparing their throughput speeds, network scalability, security against various attacks, database centrality, and the amount of resources required. The aim is to provide a comprehensive understanding of each algorithm. The language used is clear, objective, and value-neutral, with a formal register and precise word choice. The text adheres to conventional structure, including common academic sections and maintaining regular author and institution formatting. The structure is clear with a logical progression and causal connections between statements. The text is free from grammatical errors, spelling mistakes, and punctuation errors. No changes in content have been made.

Select All
1.
C S WRIGHT, "Bitcoin: A Peer-to-Peer Electronic Cash System[J/OL]", SSRN Electronic Journal, 2019, [online] Available: http://dx.doi.org/10.2139/ssrn.3440802.
2.
S M H BAMAKAN, A MOTAVALI and A BABAEI BONDARTI, "A survey of blockchain consensus algorithms performance evaluation criteria[J/OL]", Expert Systems with Applications, pp. 113385, 2020, [online] Available: http://dx.doi.org/10.1016/j.eswa.2020.113385.
3.
D MINGXIAO, M XIAOFENG, Z ZHE et al., "A review on consensus algorithm of blockchain[C/OL]", 2017 IEEE International Conference on Systems Man and Cybernetics (SMC), 2017, [online] Available: http://dx.doi.org/10.1109/smc.2017.8123011.
4.
L LAMPORT, "The part-time parliament[J/OL]", ACM Transactions on Computer Systems, pp. 133-169, 1998, [online] Available: http://dx.doi.org/10.1145/279227.279229.
5.
L LAMPORT, Paxos Made Simple[J], 2001.
6.
D ONGARO and K OUSTERHOUT John, In search of an understandable consensus algorithm[J], 2014.
7.
M CASTRO, Practical Byzantine Fault Tolerance[J], 2000.
8.
S ANGELIS, L ANIELLO, R BALDONI et al., PBFT vs proof-of-authority: applying the CAP theorem to permissioned blockchain[J], 2018.
9.
G GOLAN-GUETA, I ABRAHAM, S GROSSMAN et al., SBFT: a Scalable Decentralized Trust Infrastructure for Blockchains.[J], 2018.
10.
S GAO, T YU, J ZHU et al., "T-PBFT: An EigenTrust-based practical Byzantine fault tolerance consensus algorithm[J/OL]", China Communications, pp. 111-123, 2019, [online] Available: http://dx.doi.org/10.23919/jcc.2019.12.008.
11.
I BENTOV, C LEE, A MIZRAHI et al., "Proof of Activity[J/OL]", ACM SIGMETRICS Performance Evaluation Review, vol. 42, no. 3, pp. 34-37, 2014, [online] Available: http://dx.doi.org/10.1145/2695533.2695545.
12.
M BASTIAAN, Preventing the 51%-Attack: a Stochastic Analysis of Two Phase Proof of Work in Bitcoin[J], 2015.
13.
A ORAM, Peer-to-Peer: Harnessing the Power of Disruptive Technologies[J], 2001.
14.
M WENDL, H DOAN M and R SASSEN, "The environmental impact of cryptocurrencies using proof of work and proof of stake consensus algorithms: A systematic review[J/OL]", Journal of Environmental Management, vol. 326, pp. 116530, 2023, [online] Available: http://dx.doi.org/10.1016/j.jenvman.2022.116530.
15.
B DAVID, P GAŽI, A KIAYIAS et al., "Ouroboros Praos: An Adaptively-Secure Semi-synchronous Proof-of-Stake Blockchain[M/OL]", Advances in Cryptology – EUROCRYPT 2018Lecture Notes in Computer Science, pp. 66-98, 2018, [online] Available: http://dx.doi.org/10.1007/978-3-319-78375-8_3.
16.
A KIAYIAS, A RUSSELL, B DAVID et al., "Ouroboros: A Provably Secure Proof-of-Stake Blockchain Protocol[M/OL]", Advances in Cryptology – CRYPTO 2017Lecture Notes in Computer Science, pp. 357-388, 2017, [online] Available: http://dx.doi.org/10.1007/978-3-319-63688-7_12.
17.
F YANG, W ZHOU, Q WU et al., "Delegated Proof of Stake With Downgrade: A Secure and Efficient Blockchain Consensus Algorithm With Downgrade Mechanism[J/OL]", IEEE Access, pp. 118541-118555, 2019, [online] Available: http://dx.doi.org/10.1109/access.2019.2935149.
18.
X FAN and Q CHAI, "Roll-DPoS[C/OL]", Proceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing Networking and Services, 2018, [online] Available: http://dx.doi.org/10.1145/3286978.3287023.
19.
D STONE, "Delayed Blockchain Protocols.[J]", arXiv: Computer Science and Game TheoryarXiv: Computer Science and Game Theory, 2018.
20.
N A Akbar, A Muneer, N Elhakim et al., "Distributed Hybrid Double-Spending Attack Prevention Mechanism for Proof-of-Work and Proof-of-Stake Blockchain Consensuses[J]", Future Internet, vol. 13, 2021.
21.
X Fan and Q. Chai, "Roll-DPoS: A Randomized Delegated Proof of Stake Scheme for Scalable Blockchain-Based Internet of Things Systems[C]", the 15th EAI International Conference, 2018.
22.
M A Majumdar, M Monim and M M. Shahriyer, Blockchain based Land Registry with Delegated Proof of Stake (DPoS) Consensus in Bangladesh[J], 2020.
23.
A. Yakovenko, Solana: A new architecture for a high performance blockchain v0.8.13[J], 03 2024.
24.
L AMHERD and N LI S, TESSONE ClaudioJ. Centralised or Decentralised? Data Analysis of Transaction Network of Hedera Hashgraph[J], 2023.
25.
M ALAHMAD, I ALSHAIKHLI, A ALKANDARI et al., INFLUENCE OF HEDERA HASHGRAPH OVER BLOCKCHAIN[J].
26.
Byteball official whitepaper, Jan. 2019, [online] Available: https://obyte.org/Byteball.pdf.
27.
DagCoin official whitepaper, Jan. 2019, [online] Available: https://dagcoin.org/whitepaper.pdf.
28.
IOTA official whitepaper, Jan. 2019, [online] Available: https://assets.ctfassets.net/r1dr6vzfxhev/2t4uxvsIqk0EUau6g2sw0g/45eae33637ca92f85dd9f4a3a218e1ec/iota1_4_3.pdf.
29.
K LIU, M JOURENKO and M LARANGEIRA, Reducing Latency of DAG-based Consensus in the Asynchronous Setting via the UTXO Model[J], 2023.
30.
T Zhou, X Li and H. Zhao, "DLattice: A Permission-Less Blockchain Based on DPoS-BA-DAG Consensus for Data Tokenization[J]", IEEE Access, 2019.

Contact IEEE to Subscribe

References

References is not available for this document.