Critical Review of Blockchain Consensus Algorithms: challenges and opportunities

Authors

  • Muhammad Tahir Department of Computer Science, COMSATS University Islamabad, Attock Campus,.
  • Muhammad Sardaraz Department of Computer Science, COMSATS University Islamabad, Attock Campus,.
  • Usman Aziz Department of Computer Science, COMSATS University Islamabad, Attock Campus,.

Keywords:

Blockchain, consensus algorithms, performance evaluation, IoT, big data

Abstract

Blockchain is a distributed ledger in which transactions are grouped in blocks linked by hash pointers. Blockchain-based solutions provide trust and privacy because of the resistance to the inconsistency of data and advanced cryptographic features. In various fields, blockchain technology has been implemented to ensure transparency, verifiability, interoperability, governance, and management of information systems.  Processing large volumes of data being generated through emerging technologies is a big issue. Many researchers have used Blockchain in various fields integrated with IoT, i.e., industry 4.0, biomedical, health, genomics, etc. Blockchain has the attributes of decentralization, solidness, security, and immutability with a possibility to secure the system design for transmission and storage of data. The purpose of the consensus protocols is to keep up the security and effectiveness of the blockchain network. Utilizing the correct protocol enhances the performance of the blockchain applications. This article presents essential principles and attributes of consensus algorithms to show the applications, challenges, and opportunities of blockchain technology. Moreover, future research directions are also presented to choose an appropriate consensus algorithm to enhance the performance of Blockchain based applications

References

G. W. Peters, E. Panayi, and A. Chapelle, “Trends in Crypto-Currencies and Blockchain Technologies: A Monetary Theory and Regulation Perspective,” SSRN Electron. J., 2015, doi: 10.2139/ssrn.2646618.

G. Foroglou and A. L. Tsilidou, “Further applications of the blockchain,” Conf. 12th Student Conf. Manag. Sci. Technol. Athens, no. MAY, pp. 0–8, 2015.

A. Kosba, A. Miller, E. Shi, Z. Wen, and C. Papamanthou, “Hawk: The Blockchain Model of Cryptography and Privacy-Preserving Smart Contracts,” Proc. - 2016 IEEE Symp. Secur. Privacy, SP 2016, pp. 839–858, Aug. 2016, doi: 10.1109/SP.2016.55.

B. W. Akins, J. L. Chapman, and J. M. Gordon, “A Whole New World: Income Tax Considerations of the Bitcoin Economy,” Pittsburgh Tax Rev., vol. 12, no. 1, pp. 24–56, 2015, doi: 10.5195/taxreview.2014.32.

Y. Zhang and J. Wen, “An IoT electric business model based on the protocol of bitcoin,” 2015 18th Int. Conf. Intell. Next Gener. Networks, ICIN 2015, pp. 184–191, Mar. 2015, doi: 10.1109/ICIN.2015.7073830.

M. Sharples and J. Domingue, “The blockchain and kudos: A distributed system for educational record, reputation and reward,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 9891 LNCS, pp. 490–496, 2016, doi: 10.1007/978-3-319-45153-4_48.

C. Noyes, “BitAV: Fast Anti-Malware by Distributed Blockchain Consensus and Feedforward Scanning,” Jan. 2016, doi: 10.48550/arxiv.1601.01405.

M. Iansiti and K. R. Lakhani, “The truth about blockchain: It will take years to transform business, but the journey begins now,” Harv. Bus. Rev., no. January 2017, pp. 117–128, 2017.

H. Jang and J. Lee, “An Empirical Study on Modeling and Prediction of Bitcoin Prices with Bayesian Neural Networks Based on Blockchain Information,” IEEE Access, vol. 6, pp. 5427–5437, Nov. 2017, doi: 10.1109/ACCESS.2017.2779181.

A. Stanciu, “Blockchain Based Distributed Control System for Edge Computing,” Proc. - 2017 21st Int. Conf. Control Syst. Comput. CSCS 2017, pp. 667–671, Jul. 2017, doi: 10.1109/CSCS.2017.102.

T. T. A. Dinh, R. Liu, M. Zhang, G. Chen, B. C. Ooi, and J. Wang, “Untangling Blockchain: A Data Processing View of Blockchain Systems,” IEEE Trans. Knowl. Data Eng., vol. 30, no. 07, pp. 1366–1385, Jul. 2018, doi: 10.1109/TKDE.2017.2781227.

F. Tschorsch and B. Scheuermann, “Bitcoin and beyond: A technical survey on decentralized digital currencies,” IEEE Commun. Surv. Tutorials, vol. 18, no. 3, pp. 2084–2123, 2016, doi: 10.1109/COMST.2016.2535718.

J. Bonneau, A. Miller, J. Clark, A. Narayanan, J. A. Kroll, and E. W. Felten, “SoK: Research perspectives and challenges for bitcoin and cryptocurrencies,” Proc. - IEEE Symp. Secur. Priv., vol. 2015-July, pp. 104–121, Jul. 2015, doi: 10.1109/SP.2015.14.

M. Schäffer, M. di Angelo, and G. Salzer, “Performance and Scalability of Private Ethereum Blockchains,” Lect. Notes Bus. Inf. Process., vol. 361, no. August, pp. 103–118, 2019, doi: 10.1007/978-3-030-30429-4_8.

R. A. U. Ullah. A, Qayyum. H, Hassan. F, Khan. M. k, “Comparison of Machine Learning Algorithms for Sepsis Detection,” Int. J. Innov. Sci. Technol., vol. 4, no. 1, pp. 175–188, 2022, [Online]. Available: https://journal.50sea.com/index.php/IJIST/article/view/190

M. Anjum.S. M, Riaz.O,Latif, S, “Diastolic Dysfunction Prediction with Symptoms Using Machine Learning Approach,” Int. J. Innov. Sci. Technol., vol. 4, no. 3, pp. 714–727, 2022, [Online]. Available: https://journal.50sea.com/index.php/IJIST/article/view/280/

I. C. Lin and T. C. Liao, “A survey of blockchain security issues and challenges,” Int. J. Netw. Secur., vol. 19, no. 5, pp. 653–659, 2017, doi: 10.6633/IJNS.201709.19(5).01.

K. M. I. Baig. M. S, Imran. A, Yasin. A. U, Butt. A. H, “Natural Language to SQL Queries: A Review,” Int. J. Innov. Sci. Technol., vol. 4, no. 1, pp. 147–162, 2022.

“On Public and Private Blockchains | Ethereum Foundation Blog.” https://blog.ethereum.org/2015/08/07/on-public-and-private-blockchains/ (accessed Jul. 27, 2022).

D. H. Zaka. S, Majeed. M. N, “Blind Image Deblurring Using Laplacian of Gaussian (LoG) Based Image Prior,” Int. J. Innov. Sci. Technol., vol. 4, no. 2, pp. 365–374, 2022.

C. Decker and R. Wattenhofer, “Information propagation in the Bitcoin network,” 13th IEEE Int. Conf. Peer-to-Peer Comput. IEEE P2P 2013 - Proc., 2013, doi: 10.1109/P2P.2013.6688704.

M. Du, X. Ma, Z. Zhang, X. Wang, and Q. Chen, “A review on consensus algorithm of blockchain,” 2017 IEEE Int. Conf. Syst. Man, Cybern. SMC 2017, vol. 2017-January, pp. 2567–2572, Nov. 2017, doi: 10.1109/SMC.2017.8123011.

S. Kaur, S. Chaturvedi, A. Sharma, and J. Kar, “A Research Survey on Applications of Consensus Protocols in Blockchain,” Secur. Commun. Networks, vol. 2021, 2021, doi: 10.1155/2021/6693731.

M. Kaur, M. Z. Khan, S. Gupta, A. Noorwali, C. Chakraborty, and S. K. Pani, “MBCP: Performance Analysis of Large Scale Mainstream Blockchain Consensus Protocols,” IEEE Access, vol. 9, pp. 80931–80944, 2021, doi: 10.1109/ACCESS.2021.3085187.

S. Bouraga, “A taxonomy of blockchain consensus protocols: A survey and classification framework,” Expert Syst. Appl., vol. 168, p. 114384, Apr. 2021, doi: 10.1016/J.ESWA.2020.114384.

A. Singh, G. Kumar, R. Saha, M. Conti, M. Alazab, and R. Thomas, “A survey and taxonomy of consensus protocols for blockchains,” J. Syst. Archit., vol. 127, p. 102503, Jun. 2022, doi: 10.1016/J.SYSARC.2022.102503.

A. Altarawneh, F. Sun, R. R. Brooks, O. Hambolu, L. Yu, and A. Skjellum, “Availability analysis of a permissioned blockchain with a lightweight consensus protocol,” Comput. Secur., vol. 102, p. 102098, Mar. 2021, doi: 10.1016/J.COSE.2020.102098.

D. P. Oyinloye, J. Sen Teh, N. Jamil, and M. Alawida, “Blockchain Consensus: An Overview of Alternative Protocols,” Symmetry 2021, Vol. 13, Page 1363, vol. 13, no. 8, p. 1363, Jul. 2021, doi: 10.3390/SYM13081363.

B. Sriman, S. Ganesh Kumar, and P. Shamili, “Blockchain Technology: Consensus Protocol Proof of Work and Proof of Stake,” Adv. Intell. Syst. Comput., vol. 1172, no. March 2022, pp. 395–406, 2021, doi: 10.1007/978-981-15-5566-4_34.

H. Afzaal, M. Imran, M. U. Janjua, and S. P. Gochhayat, “Formal Modeling and Verification of a Blockchain-Based Crowdsourcing Consensus Protocol,” IEEE Access, vol. 10, pp. 8163–8183, 2022, doi: 10.1109/ACCESS.2022.3141982.

M. Sun, Y. Lu, Y. Feng, Q. Zhang, and S. Liu, “Modeling and verifying the CKB blockchain consensus protocol,” Mathematics, vol. 9, no. 22, pp. 1–15, 2021, doi: 10.3390/math9222954.

G. A. F. Rebello, G. F. Camilo, L. C. B. Guimarães, L. A. C. de Souza, G. A. Thomaz, and O. C. M. B. Duarte, “A security and performance analysis of proof-based consensus protocols,” Ann. Telecommun. 2021, pp. 1–21, Nov. 2021, doi: 10.1007/S12243-021-00896-2.

A. A. Siyal, A. Z. Junejo, M. Zawish, K. Ahmed, A. Khalil, and G. Soursou, “Applications of blockchain technology in medicine and healthcare: Challenges and future perspectives,” Cryptography, vol. 3, no. 1, pp. 1–16, 2019, doi: 10.3390/cryptography3010003.

E. Filatovas, M. Marcozzi, L. Mostarda, and R. Paulavičius, “A MCDM-based framework for blockchain consensus protocol selection,” Expert Syst. Appl., vol. 204, p. 117609, Oct. 2022, doi: 10.1016/J.ESWA.2022.117609.

Y. Zhan, B. Wang, R. Lu, and Y. Yu, “DRBFT: Delegated randomization Byzantine fault tolerance consensus protocol for blockchains,” Inf. Sci. (Ny)., vol. 559, pp. 8–21, Jun. 2021, doi: 10.1016/J.INS.2020.12.077.

Z. Ren, H. Xiang, Z. Zhou, N. Wang, and H. Jin, “AlphaBlock: An evaluation framework for blockchain consensus algorithms,” SBC 2021 - Proc. 9th Int. Work. Secur. Blockchain Cloud Comput. co-located with ASIA CCS 2021, pp. 17–22, May 2021, doi: 10.1145/3457977.3460297.

S. Y. Jin and Y. Xia, “CEV Framework: A Central Bank Digital Currency Evaluation and Verification Framework With a Focus on Consensus Algorithms and Operating Architectures,” IEEE Access, vol. 10, pp. 63698–63714, Jun. 2022, doi: 10.1109/ACCESS.2022.3183092.

F. Xiang, W. Huaimin, S. Peichang, O. Xue, and Z. Xunhui, “Jointgraph: A DAG-based efficient consensus algorithm for consortium blockchains,” Softw. Pract. Exp., vol. 51, no. 10, pp. 1987–1999, Oct. 2021, doi: 10.1002/SPE.2748.

H. Samy, A. Tammam, A. Fahmy, and B. Hasan, “Enhancing the performance of the blockchain consensus algorithm using multithreading technology,” Ain Shams Eng. J., vol. 12, no. 3, pp. 2709–2716, Sep. 2021, doi: 10.1016/J.ASEJ.2021.01.019.

H. Moradian and S. S. Kia, “a Study on Accelerating Average Consensus Algorithms Using Delayed Feedback,” IEEE Trans. Control Netw. Syst., pp. 1–11, 2022, doi: 10.1109/TCNS.2022.3188481.

P. Wang, W. Chen, and Z. Sun, “Consensus algorithm based on verifiable randomness,” Inf. Sci. (Ny)., vol. 608, pp. 844–857, Aug. 2022, doi: 10.1016/J.INS.2022.07.024.

M. Kara et al., “A Compute and Wait in PoW (CW-PoW) Consensus Algorithm for Preserving Energy Consumption,” Appl. Sci. 2021, Vol. 11, Page 6750, vol. 11, no. 15, p. 6750, Jul. 2021, doi: 10.3390/APP11156750.

P. Prabha and K. Chatterjee, “Design and implementation of hybrid consensus mechanism for IoT based healthcare system security,” Int. J. Inf. Technol., vol. 14, no. 3, pp. 1381–1396, May 2022, doi: 10.1007/S41870-022-00880-6/FIGURES/9.

A. S. Sajjad. S, Abdullah. A, Arif. M, Faisal. M. U, Ashraf. M. D, “A Comparative Analysis of Camera, LiDAR and Fusion Based Deep Neural Networks for Vehicle Detection,” Int. J. Innov. Sci. Technol., vol. 3, no. special issue, pp. 177–186, 2021.

L. M. Bach, B. Mihaljevic, and M. Zagar, “Comparative analysis of blockchain consensus algorithms,” 2018 41st Int. Conv. Inf. Commun. Technol. Electron. Microelectron. MIPRO 2018 - Proc., pp. 1545–1550, Jun. 2018, doi: 10.23919/MIPRO.2018.8400278.

H. F. Ouattara, D. Ahmat, F. T. Ouédraogo, T. F. Bissyandé, and O. Sié, “Blockchain consensus protocols: Towards a review of practical constraints for implementation in developing countries,” Lect. Notes Inst. Comput. Sci. Soc. Telecommun. Eng. LNICST, vol. 250, pp. 304–314, 2018, doi: 10.1007/978-3-319-98827-6_29/COVER.

C. Natoli and V. Gramoli, “The Balance Attack or Why Forkable Blockchains are Ill-Suited for Consortium,” Proc. - 47th Annu. IEEE/IFIP Int. Conf. Dependable Syst. Networks, DSN 2017, no. December, pp. 579–590, 2017, doi: 10.1109/DSN.2017.44.

C. Dannen, Cryptoeconomics Survey. 2017. doi: 10.1007/978-1-4842-2535-6_7.

R. O. and S. W. Anjum. M. S, Mumtaz. S, “Heart Attack Risk Prediction with Duke Treadmill Score with Symptoms using Data Mining,” Int. J. Innov. Sci. Technol., vol. 3, no. 4, pp. 174–185, 2021.

R. A. Manzoor. S, Qayyum. H, Hassan. F, Ullah. A, Nawaz. A, “Melanoma Detection Using a Deep Learning Approach,” Int. J. Innov. Sci. Technol., vol. 4, no. 1, pp. 222–232, 2022.

L. Fan and H.-S. Zhou, “A Scalable Proof-of-Stake Blockchain in the Open Setting ∗ (or, How to Mimic Nakamoto’s Design via Proof-of-Stake),” Cryptol. ePrint Arch., 2018, [Online]. Available: https://eprint.iacr.org/2017/656.pdf

“Comparison of Ethereum, Hyperledger Fabric and Corda | by Philipp Sandner | Medium.” https://philippsandner.medium.com/comparison-of-ethereum-hyperledger-fabric-and-corda-21c1bb9442f6 (accessed Jul. 27, 2022).

L. Chen, L. Xu, N. Shah, Z. Gao, Y. Lu, and W. Shi, “On security analysis of proof-of-elapsed-time (PoET),” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 10616 LNCS, pp. 282–297, 2017, doi: 10.1007/978-3-319-69084-1_19/COVER.

E. Androulaki et al., “Hyperledger Fabric: A Distributed Operating System for Permissioned Blockchains,” Proc. 13th EuroSys Conf. EuroSys 2018, vol. 2018-January, Apr. 2018, doi: 10.1145/3190508.3190538.

J. Sousa, A. Bessani, and M. Vukolic, “A byzantine Fault-Tolerant ordering service for the hyperledger fabric blockchain platform,” Proc. - 48th Annu. IEEE/IFIP Int. Conf. Dependable Syst. Networks, DSN 2018, no. June, pp. 51–58, 2018, doi: 10.1109/DSN.2018.00018.

D. Mazi`eres and M. Mazi`eres, “The Stellar Consensus Protocol: A Federated Model for Internet-level Consensus”.

M. Liu, F. R. Yu, Y. Teng, V. C. M. Leung, and M. Song, “Joint computation offloading and content caching for wireless blockchain networks,” INFOCOM 2018 - IEEE Conf. Comput. Commun. Work., pp. 517–522, Jul. 2018, doi: 10.1109/INFCOMW.2018.8406929.

W. Wang et al., “A Survey on Consensus Mechanisms and Mining Strategy Management in Blockchain Networks,” IEEE Access, vol. 7, pp. 22328–22370, 2019, doi: 10.1109/ACCESS.2019.2896108.

Downloads

Published

2022-06-30

How to Cite

Tahir, M., Sardaraz, M., & Aziz, U. (2022). Critical Review of Blockchain Consensus Algorithms: challenges and opportunities. International Journal of Innovations in Science & Technology, 4(5), 52–64. Retrieved from https://journal.50sea.com/index.php/IJIST/article/view/314