Volume 7 • Issue 1 • PP: 19-33 • 2022
An Efficient decision-making model of consensus protocols for blockchains: An exploratory study
View PDF Abstract
In addition to being a game-changer for the cryptocurrency business, Blockchain was also a catalyst for the fast rise of certain Distributed Ledger Technologies (DLTs). An important aspect of a DLT system's design is a consensus mechanism, which ensures that almost all interviewees agreed on the integrity of the data. As a result, a broad variety of consensus protocols have been developed, each with a distinct notion and property (e.g., reduced energy usage, greater scalability). When moving from one blockchain network to another, the main criteria for consensus mechanisms typically vary dramatically, so there is no universal protocol. As a result, choosing the best consensus mechanism for a certain DLT system is critical, but also difficult, since experts must balance competing demands. MCDM approaches are used in this research to provide an approach for choosing the best consensus procedures based on criteria, objectives, and other needs. A genuine bike-rental application is used to show the technology's potential, as well as the preferred consensus mechanisms for 3 of the most popular kinds of current blockchain systems. To top it all off, the information and technologies gathered are openly accessible for anybody to use, allowing for maximum replication and future improvement.
Keywords
References
[1] S. Nakamoto, “Bitcoin: A peer-to-peer electronic cash system,” Decentralized Business Review, p. 21260, 2008.
[2] M. Belotti, N. Božić, G. Pujolle, and S. Secci, “A vademecum on blockchain technologies: When, which, and how,” IEEE Communications Surveys & Tutorials, vol. 21, no. 4, pp. 3796–3838, 2019.
[3] D. Berdik, S. Otoum, N. Schmidt, D. Porter, and Y. Jararweh, “A survey on blockchain for information systems management and security,” Information Processing & Management, vol. 58, no. 1, p. 102397, 2021.
[4] J. Kolb, M. AbdelBaky, R. H. Katz, and D. E. Culler, “Core concepts, challenges, and future directions in blockchain: A centralized tutorial,” ACM Computing Surveys (CSUR), vol. 53, no. 1, pp. 1–39, 2020.
[5] R. Paulavičius, S. Grigaitis, A. Igumenov, and E. Filatovas, “A decade of blockchain: Review of the current status, challenges, and future directions,” Informatica, vol. 30, no. 4, pp. 729–748, 2019.
[6] U. Bodkhe et al., “Blockchain for industry 4.0: A comprehensive review,” IEEE Access, vol. 8, pp. 79764–79800, 2020.
[7] L. Lao, Z. Li, S. Hou, B. Xiao, S. Guo, and Y. Yang, “A survey of IoT applications in blockchain systems: Architecture, consensus, and traffic modeling,” ACM Computing Surveys (CSUR), vol. 53, no. 1, pp. 1–32, 2020.
[8] M. Pournader, Y. Shi, S. Seuring, and S. C. L. Koh, “Blockchain applications in supply chains, transport and logistics: a systematic review of the literature,” International Journal of Production Research, vol. 58, no. 7, pp. 2063–2081, 2020.
[9] R. Paulavičius, S. Grigaitis, and E. Filatovas, “A systematic review and empirical analysis of blockchain simulators,” IEEE access, vol. 9, pp. 38010–38028, 2021.
[10] S. Bano et al., “SoK: Consensus in the age of blockchains,” in Proceedings of the 1st ACM Conference on Advances in Financial Technologies, 2019, pp. 183–198.
[11] S. M. H. Bamakan, A. Motavali, and A. B. Bondarti, “A survey of blockchain consensus algorithms performance evaluation criteria,” Expert Systems with Applications, vol. 154, p. 113385, 2020.
[12] D. Mingxiao, M. Xiaofeng, Z. Zhe, W. Xiangwei, and C. Qijun, “A review on consensus algorithm of blockchain,” in 2017 IEEE international conference on systems, man, and cybernetics (SMC), 2017, pp. 2567–2572.
[13] S. Zhang and J.-H. Lee, “Analysis of the main consensus protocols of blockchain,” ICT express, vol. 6, no. 2, pp. 93–97, 2020.
[14] Y. Xiao, N. Zhang, W. Lou, and Y. T. Hou, “A survey of distributed consensus protocols for blockchain networks,” IEEE Communications Surveys & Tutorials, vol. 22, no. 2, pp. 1432–1465, 2020.
[15] A. Berentsen, “Aleksander Berentsen Recommends ‘Bitcoin: A Peer-to-Peer Electronic Cash System’ by Satoshi Nakamoto,” in 21st Century Economics, Springer, 2019, pp. 7–8.
[16] S. Bouraga, “A taxonomy of blockchain consensus protocols: A survey and classification framework,” Expert Systems with Applications, vol. 168, p. 114384, 2021.
[17] N. Chalaemwongwan and W. Kurutach, “Notice of Violation of IEEE Publication Principles: State of the art and challenges facing consensus protocols on blockchain,” in 2018 International Conference on Information Networking (ICOIN), 2018, pp. 957–962.
[18] X. Fu, H. Wang, and P. Shi, “A survey of Blockchain consensus algorithms: mechanism, design and applications,” Science China Information Sciences, vol. 64, no. 2, pp. 1–15, 2021.
[19] J. Nijsse and A. Litchfield, “A taxonomy of blockchain consensus methods,” Cryptography, vol. 4, no. 4, p. 32, 2020.
[20] S. Wan, M. Li, G. Liu, and C. Wang, “Recent advances in consensus protocols for blockchain: a survey,” Wireless networks, vol. 26, no. 8, pp. 5579–5593, 2020.
[21] M. Salimitari and M. Chatterjee, “A survey on consensus protocols in blockchain for iot networks,” arXiv preprint arXiv:1809.05613, 2018.
[22] T. Gal, T. Stewart, and T. Hanne, Multicriteria decision making: advances in MCDM models, algorithms, theory, and applications, vol. 21. Springer Science & Business Media, 2013.
[23] I. M. Ar, I. Erol, I. Peker, A. I. Ozdemir, T. D. Medeni, and I. T. Medeni, “Evaluating the feasibility of blockchain in logistics operations: A decision framework,” Expert Systems with Applications, vol. 158, p. 113543, 2020.
[24] S. Farshidi, S. Jansen, S. España, and J. Verkleij, “Decision support for blockchain platform selection: Three industry case studies,” IEEE transactions on Engineering management, vol. 67, no. 4, pp. 1109–1128, 2020.
[25] A. Baliga, “Understanding blockchain consensus models,” Persistent, vol. 4, no. 1, p. 14, 2017.
[26] G.-T. Nguyen and K. Kim, “A survey about consensus algorithms used in blockchain,” Journal of Information processing systems, vol. 14, no. 1, pp. 101–128, 2018.
[27] G. O. Odu, “Weighting methods for multi-criteria decision making technique,” Journal of Applied Sciences and Environmental Management, vol. 23, no. 8, pp. 1449–1457, 2019.
[28] Y.-L. Wang and G.-H. Tzeng, “Brand marketing for creating brand value based on a MCDM model combining DEMATEL with ANP and VIKOR methods,” Expert systems with applications, vol. 39, no. 5, pp. 5600–5615, 2012.
Cite This Article
Choose your preferred format