Abstract
Day-by-day, both data and network size are growing at a rapid rate. It is essential to keep private data secure and also prevent malicious activities. In a permissionless blockchain, nodes do not take permission for participation. One can directly mine a block by performing an open task. Security can be a significant issue here. Also, there is no third-party involvement in blockchain, so keeping trust among peers is an essential feature. The distributed public ledger stores history of old transactions to maintain trust between peers. To prevent malicious activities, consensus algorithms are used, which are defined as a complex task that a miner must perform to mine new blocks into the blockchain. In this chapter, various consensus mechanisms are mentioned with merits and demerits. With high computation power and digital currencies, nodes can quickly get into the blockchain and perform malicious activities. For that, various consensus algorithms are used like Proof of Work (PoW), Proof of Stake (PoS), Proof of Burn (PoB), Proof of Capacity (PoC), etc. Every consensus is developed to solve issues of previously developed consensus and provide more efficiency concerning resource allocation, scalability, security against attacks, power consumption, etc. Bitcoin is one of the use cases of blockchain, which is developed upon the PoW consensus method. Various companies have developed cryptocurrencies that are based on consensus algorithms. Consensus can be implemented on smart contracts to govern specific rules in the blockchain. While working with extensive transactions and a large chain of blocks, scalability, efficiency, and malicious attacks are significant issues. We have done a comparative analysis of all the consensus algorithms based on such issues.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bodkhe U, Mehta D, Tanwar S, Bhattacharya P, Singh PK, Hong W-C (2020) A survey on decentralized consensus mechanisms for cyber physical systems. IEEE Access 8:54371–54401. https://doi.org/10.1109/ACCESS.2020.2981415
Zheng Z, Xie S, Dai H, Chen X, Wang H (2017) An overview of blockchain technology: architecture, consensus, and future trends. IEEE Int Congr Big Data (BigData Congr) 2017:557–564. https://doi.org/10.1109/BigDataCongress.2017.85
Bach LM, Mihaljevic B, Zagar M (2018) Comparative analysis of blockchain consensus algorithms. In: 41st international convention on information and communication technology, electronics and microelectronics (MIPRO), pp 1545–1550. https://doi.org/10.23919/MIPRO.2018.8400278
Gupta R, Nair A, Tanwar S, Kumar N (2020) Blockchain-assisted secure UAV communication in 6G environment: architecture, opportunities, and challenges. IET Commun. https://doi.org/10.1049/cmu2.12113
Zou W, Lo D, Kochhar PS, Le XBD, Xia X, Feng Y, Chen Z, Xu B (2019) Smart contract development: challenges and opportunities. IEEE Trans Softw Eng
Cachin C, Vukolić M (2017) Blockchain consensus protocols in the wild. arXiv:1707.01873
Shaik VA, Malik P, Singh R, Gehlot A, Tanwar S (2020) Adoption of blockchain technology in various realms: opportunities and challenges. Secur Priv 3:e109. https://doi.org/10.1002/spy2.109
Berman P, Garay JA, Perry KJ (1989) Towards optimal distributed consensus. In: FOCS, vol 89, pp 410–415
Amelchenko M, Dolev S (2017) Blockchain abbreviation: implemented by message passing and shared memory. In: 2017 IEEE 16th international symposium on network computing and applications (NCA). IEEE, pp 1–7
Wright A, De Filippi P (2015) Decentralized blockchain technology and the rise of lex cryptographia. Available at SSRN 2580664
Baudet M, Ching A, Chursin A, Danezis G, Garillot F, Li Z, Malkhi D, Naor O, Perelman D, Sonnino A (2019) State machine replication in the libra blockchain. The Libra Assn, Technical report
Fan K, Sun S, Yan Z, Pan Q, Li H, Yang Y (2019) A blockchain-based clock synchronization scheme in IoT. Futur Gener Comput Syst 101:524–533
Fischer MJ (1983) The consensus problem in unreliable distributed systems (a brief survey). In: International conference on fundamentals of computation theory. Springer, Berlin, pp 127–140
Barborak M, Dahbura A, Malek M (1993) The consensus problem in fault-tolerant computing. ACM Comput Surv (CSur) 25(2):171–220
Shah MA, Hellerstein JM, Brewer E (2004) Highly available, fault-tolerant, parallel dataflows. In: Proceedings of the 2004 ACM SIGMOD international conference on management of data, pp 827–838
Yanovich Y, Ivashchenko I, Ostrovsky A, Shevchenko A, Sidorov A (2018) Exonum: byzantine fault tolerant protocol for blockchains. bitfury. com, pp 1–36
Ferdous MS, Chowdhury MJM, Hoque MA, Colman A (2020) Blockchain consensus algorithms: a survey. arXiv:2001.07091
Hoffman RS, Hoffman R (2000) Does consensus equal correctness? J Toxicol: Clin Toxicol 38(7):689–690
Mostefaoui A, Raynal M (2001) Leader-based consensus. Parallel Process Lett 11(01):95–107
Zhang L, Li Q (2018) Research on consensus efficiency based on practical byzantine fault tolerance. In: 2018 10th international conference on modelling, identification and control (ICMIC). IEEE, pp 1–6
Mingxiao D, Xiaofeng M, Zhe Z, Xiangwei W, Qijun C (2017) A review on consensus algorithm of blockchain. In: IEEE international conference on systems, man, and cybernetics (SMC), pp 2567–2572
Helliar CV, Crawford L, Rocca L, Teodori C, Veneziani M (2020) Permissionless and permissioned blockchain diffusion. Int J Inf Manag 54:102136
Gupta R, Kumari A, Tanwar S (2020) A taxonomy of blockchain envisioned edge-as-a-connected autonomous vehicles. Trans Emerg Telecommun Technol. https://doi.org/10.1002/ett.4009
Rizal BF, Ubacht J, Janssen M (2019) Unraveling transparency and accountability in blockchain. In: Proceedings of the 20th annual international conference on digital government research, pp 204–213
Mitani T, Otsuka A (2020) Traceability in permissioned blockchain. IEEE Access 8:21573–21588
Gupta R, Aparna K, Sudeep T, Neeraj K (2020) Blockchain-envisioned softwarized multi-swarming UAVs to tackle COVID-19 situations. IEEE Netw. https://doi.org/10.1109/MNET.011.2000439
Nakamoto S (2008) Bitcoin: a peer-to-peer electronic cash system. Decentralized Bus Rev 21260
Stinson DR (2006) Some observations on the theory of cryptographic hash functions. Des, Codes Cryptogr 38(2):259–277
Natoli C, Gramoli V (2016) The blockchain anomaly. In: 2016 IEEE 15th international symposium on network computing and applications (NCA). IEEE, pp 310–317
Karame GO, Androulaki E, Capkun S (2012) Double-spending fast payments in bitcoin. In: Proceedings of the 2012 ACM conference on computer and communications security, pp 906–917
Douceur JR (2002) The sybil attack. In: International workshop on peer-to-peer systems. Springer, Berlin, pp 251–260
Jamal T, Haider Z, Butt SA, Chohan A (2018) Denial of service attack in cooperative networks. arXiv:1810.11070
Zhou X, Dong J, Zhang X, Zhang P (2018) Application of blockchain technology in the financial industry and its legal norms. In: 2018 2nd international conference on man, education and social science. Atlantis Press
Nguyen CT, Hoang DT, Nguyen DN, Niyato D, Nguyen HT, Dutkiewicz E (2019) Proof-of-stake consensus mechanisms for future blockchain networks: fundamentals, applications and opportunities. IEEE Access 7:85727–85745
King S, Nadal S (2012) PPCoin: Peer-to-peer crypto-currency with proof-of-stake. self-published paper, 19 Aug, no 1
Ye C, Li G, Cai H, Gu Y, Fukuda A (2018) Analysis of security in blockchain: case study in 51%-attack detecting. In: 2018 5th international conference on dependable systems and their applications (DSA). IEEE, pp 15–24
Li W, Andreina S, Bohli J-M, Karame G (2017) Securing proof-of-stake blockchain protocols. In: Data privacy management, cryptocurrencies and blockchain technology. Springer, Cham, pp 297–315
Azouvi S, McCorry P, Meiklejohn S (2018) Betting on blockchain consensus with fantomette. arXiv:1805.06786
Larimer D (2014) Delegated proof-of-stake (DPoS). Bitshare whitepaper 81:85
Salimitari M, Chatterjee M (2018) An overview of blockchain and consensus protocols for IoT networks, pp 1–12. arXiv:1809.05613
Bamakan SMH, Motavali A, Bondarti AB (2020) A survey of blockchain consensus algorithms performance evaluation criteria. Expert Syst Appl 154:113385
Ren L (2014) Proof of stake velocity: building the social currency of the digital age. Self-published white paper
Karantias K, Kiayias A, Zindros D (2020) Proof-of-burn. In: International conference on financial cryptography and data security. Springer, Cham, pp 523–540
Bach LM, Mihaljevic B, Zagar M (2018) Comparative analysis of blockchain consensus algorithms. In: 2018 41st international convention on information and communication technology, electronics and microelectronics (MIPRO). IEEE, pp 1545–1550
Azab A, Layton R, Alazab M, Oliver J (2014) Mining malware to detect variants. In: 2014 fifth cybercrime and trustworthy computing conference. IEEE, pp 44–53
Bentov I, Lee C, Mizrahi A, Rosenfeld M (2014) Proof of activity: extending bitcoin’s proof of work via proof of stake [extended abstract] y. ACM SIGMETRICS Perform Eval Rev 42(3):34–37
Goldin D, Raisch J (2013) On the weight controllability of consensus algorithms. In: 2013 European control conference (ECC). IEEE, pp 233–238
Sabt M, Achemlal M, Bouabdallah A (2015) Trusted execution environment: what it is, and what it is not. In: 2015 IEEE Trustcom/BigDataSE/ISPA, vol 1. IEEE, pp 57–64
Milutinovic M, He W, Wu H, Kanwal M (2016) Proof of luck: an efficient blockchain consensus protocol. In: Proceedings of the 1st workshop on system software for trusted execution, pp 1–6
Abreu PW, Aparicio M, Costa CJ (2018) Blockchain technology in the auditing environment. In: 2018 13th Iberian conference on information systems and technologies (CISTI). IEEE, pp 1–6
Bao S, Cao Y, Lei A, Asuquo P, Cruickshank H, Sun Z, Huth M (2019) Pseudonym management through blockchain: cost-efficient privacy preservation on intelligent transportation systems. IEEE Access 7:80390–80403
Chopra K, Gupta K, Lambora A (2019) Proof of existence using blockchain. In: 2019 international conference on machine learning, big data, cloud and parallel computing (COMITCon). IEEE, pp 429–431
Bada AO, Damianou A, Angelopoulos CM, Katos V (2021) Towards a green blockchain: a review of consensus mechanisms and their energy consumption. In: 2021 17th international conference on distributed computing in sensor systems (DCOSS). IEEE, pp 503–511
Yakovenko A (2018) Solana: a new architecture for a high performance blockchain v0. 8.13. Whitepaper
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Tanwar, S. (2022). Distributed Consensus for Permissionless Environment. In: Blockchain Technology. Studies in Autonomic, Data-driven and Industrial Computing. Springer, Singapore. https://doi.org/10.1007/978-981-19-1488-1_6
Download citation
DOI: https://doi.org/10.1007/978-981-19-1488-1_6
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-19-1487-4
Online ISBN: 978-981-19-1488-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)