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Enhancing the performance of permissionless blockchain networks through randomized message-based consensus algorithm

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Abstract

A public blockchain network ensures security, performance, and integrity through its consensus algorithm. However, most public blockchain consensus algorithms require intensive resources such as; energy, CPU, stake, and memory. Further, the incentive mechanisms of most permissionless consensus algorithms are biased towards the miners having the most resources. This paper proposes a novel, resource-efficient, and fair rewarding consensus algorithm called Proof of Fit (PoF). The PoF consensus algorithm replaces the resource-intensive computation in Proof of Work (PoW) with massage-based resource-efficient computation called fitting-competition. We estimated the average computation time by developing a peer-to-peer messaging and computing network. Then we customized a public blockchain simulation framework to assess the performance parameters of the consensus algorithm. We did several experiments and compared the simulation results of PoF with PoW, Proof of Activity (PoA), Proof of Stake (PoS), and Poof of Capacity (PoC). The simulation result shows that the PoF consensus algorithm improves throughput by 1257%, 69%, 35%, and 18%, respectively; besides, it improves security, resource efficiency, and incentive distribution.

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References

  1. Nakamoto S (2008) Bitcoin: a peer-to-peer electronic cash system. Decentralized Business Review 21260

  2. Musleh AS, Yao G, Muyeen SM (2019) Blockchain applications in smart grid-review and frameworks. IEEE Access 7:86746–86757

    Article  Google Scholar 

  3. Taylor PJ, Dargahi T, Dehghantanha A, Parizi RM, Choo K (2020) A systematic literature review of blockchain cyber security. Digit Commun Netw 6(2):147–156

    Article  Google Scholar 

  4. Li Y, Qiao L, Lv Z (2021) An optimized Byzantine fault tolerance algorithm for consortium blockchain. 14:2826–2839

  5. Kim J (2020) Blockchain technology and its applications: case studies. 10:83–93

  6. Ismail L, Materwala H (2019) A review of blockchain architecture and consensus protocols: Use cases, challenges, and solutions. Symmetry 11(10):1198

    Article  Google Scholar 

  7. Smith SE (2020) Blockchain for future smart grid: a comprehensive survey. 8:18–43

  8. Gatteschi V, Lamberti F, Demartini, C (1992) Blockchain technology use cases. In: Kim CGS, Deka (ed) Advanced Applications of Blockchain Technology. Springer, pp 91–114

  9. Liu W, Li Y, Wang X, Peng Y, She W, Tian Z (2021) A donation tracing blockchain model using improved DPOS consensus algorithm. Peer-to-Peer Netw Appl 14(5):2789–2800

    Article  Google Scholar 

  10. Saad M, Choi J, Nyang D, Kim J, Mohaisen A (2019) Toward characterizing blockchain-based cryptocurrencies for highly accurate predictions. IEEE Syst J 14(1):321–332

    Article  Google Scholar 

  11. Alexopoulos C, Charalabidis Y, Androutsopoulou A, Loutsaris MA, Lachana Z (2019) Benefits and obstacles of blockchain applications in e-government. Paper presented at Proceedings of the 52nd Hawaii International Conference on System Sciences, 8-9 January 2019

  12. Yadav AS, Kushwaha DS (2021) Blockchain-based digitization of land record through trust value-based consensus algorithm. Peer Peer Netw Appl 14(6):3540–3558

    Article  Google Scholar 

  13. Nguewo N, Rhode G, Ologeanu-Taddei R, Lartigau J, Bourdon I (2020) A use case of blockchain in healthcare: allergy card. In: Horst T, Trevor C (eds) Blockchain and Distributed Ledger Technology Use Cases. Springer, Vienna, Austria, pp 69–94

  14. Liao D, Li H, Wang W, Wang X, Zhang M, Chen X (2021) Achieving iot data security based blockchain. Peer Peer Netw Appl 14(5):2694–2707

    Article  Google Scholar 

  15. Wu Y, Meng W, Yan Z, Varadharajan V (2020) Special issue on blockchain and communication networks. Digit Commun Netw 6(2):145–146

    Article  Google Scholar 

  16. Niranjanamurthy M, Nithya B, Jagannatha S (2019) Analysis of blockchain technology: pros, cons and SWOT. Cluster Comp 22(6):14743–14757

    Article  Google Scholar 

  17. Bao J, He D, Luo M, Choo KR (2020) A survey of blockchain applications in the energy sector. IEEE Syst J 15(3):3370–3381

    Article  Google Scholar 

  18. Abishu HN, Seid AM, Yacob YH, Ayall T, Sun G, Liu G (2021) Consensus mechanism for blockchain-enabled vehicle-to-vehicle energy trading in the internet of electric vehicles. IEEE Trans Veh Technol 71(1):946–960

    Article  Google Scholar 

  19. Bamakan SMH, Motavali A, Bondarti AB (2020) A survey of blockchain consensus algorithms performance evaluation criteria. Expert Syst Appl 154:113385

  20. Xu H, Klaine PV, Onireti O, Cao B, Imran M, Zhang L (2020) Blockchain-enabled resource management and sharing for 6G communications. Digit Commun Netw 6(3):261–269

    Article  Google Scholar 

  21. 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

    Article  Google Scholar 

  22. Kaur A, Nayyar A, Singh P (2020) Blockchain: a path to the future. Cryptocur and Block Tech Appl 25–42

  23. Bach LM, Mihaljevic B, Zagar M (2018) Comparative analysis of blockchain consensus algorithms. Paper presented at the 2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) 21–25 May

  24. Mingxiao D, Xiaofeng M, Zhe Z, Xiangwei W, Qijun C (2017) A review on consensus algorithm of blockchain. A Paper presented in 2017 IEEE international conference on systems, man, and cybernetics (SMC) 5–8 October 2017

  25. Qiao L, Dang S, Shihada B, Alouini M, Nowak R, Lv Z (2021) Can blockchain link the future? Digit Commun Netw

  26. Aderibole A, Aljarwan A, Rehman MH, Zeineldin H, Mezher T, Salah K, Damiani E, Svetinovic D (2020) Blockchain technology for smart grids: decentralized NIST conceptual model of a nonlocal single photon. IEEE Access 8:43177–43190

    Article  Google Scholar 

  27. Berenjian S, Shajari M, Farshid N, Hatamian M (2016) Intelligent automated intrusion response system based on fuzzy decision making and risk assessment. A Paper presented in 2016 IEEE 8th International Conference on Intelligent Systems (IS), 04–06 September

  28. Naghizadeh A, Berenjian S, Meamari E, Atani RE (2016) Structural-based tunneling: preserving mutual anonymity for circular p2p networks. Int J Commun Syst 29(3):602–619

    Article  Google Scholar 

  29. Naghizadeh A, Berenjian S, Razeghi B, Shahanggar S, Pour NR (2015) Preserving receiver’s anonymity for circular structured P2P networks. A Paper presented In In 2015 12th Annual IEEE Consumer Communications and Networking Conference (CCNC), 9–12 January

  30. Feng X, Shi Q, Xie Q, Liu L (2021) An efficient privacy-preserving authentication model based on blockchain for Vanets. Jour Sys Arch 117:102158

  31. Chen Y, Xie H, Lv K, Wei S, Hu C (2019) Deplest: a blockchain-based privacy-preserving distributed database toward user behaviors in social networks. Inf Sci 501:100–117

    Article  Google Scholar 

  32. Balaji BS, Raja PV, Nayyar A, Sanjeevikumar P, Pandiyan S (2020) Enhancement of security and handling the inconspicuousness in IoT using a simple size extensible blockchain. Energies 13(7):1795

    Article  Google Scholar 

  33. Nguyen G, Kim K (2018) A survey about consensus algorithms used in blockchain. J Inf Process Syst 14(1):101–128

    Google Scholar 

  34. Zhuang P, Zamir T, Liang H (2020) Blockchain for cybersecurity in smart grid: a comprehensive survey. IEEE Trans Industr Inform 11(1):3–19

  35. Li K, Li H, Wang H, An H, Lu P, Yi P, Zhu F (2020) Pov: an efficient voting-based consensus algorithm for consortium blockchains. Frontiers Blockchain 3:11

    Article  Google Scholar 

  36. Chaudhry N, Yousaf MM (2018) Consensus algorithms in blockchain: comparative analysis, challenges and opportunities. Paper presented at the 12th International Conference on Open Source Systems and Technologies (ICOSST), Lahore, Pakistan, 19–21 December

  37. Bentov I, Lee C, Mizrahi A, Rosenfeld M (2014) Proof of activity: extending Bitcoin’s proof of work via proof of stake. Perform Eval Rev 42:34–37

    Article  Google Scholar 

  38. Gennaro R, Robshaw M (2015) Crypto 2015. Berlin, Heidelberg, pp 763–780

  39. Berenjian S, Hajizadeh S, Atani RE (2019) An incentive security model to provide fairness for peer-to-peer networks. A Paper presented in 2019 IEEE Conference on Application, Information and Network Security (AINS), 19–21 November

  40. Chang Z, Guo W, Guo X, Zhou Z, Ristaniemi T (2020) Incentive mechanism for edge-computing-based blockchain. IEEE Trans Industr Inform 16(11):7105–7114

    Article  Google Scholar 

  41. Xuan S, Zheng L, Chung I, Wang W, Man D, Du X, Yang W, Guizani M (2020) An incentive mechanism for data sharing based on blockchain with smart contracts. Comput Electr Eng 83:106587

  42. Guo G, Zhu Y, Chen E, Zhu G, Ma D, Chu W (2022) Continuous improvement of script-driven verifiable random functions for reducing computing power in blockchain consensus protocols. Peer Peer Netw Appl 15(1):304–323

    Article  Google Scholar 

  43. Altarawneh A, Herschberg T, Medury S, Kandah F, Skjellum A (2020) Buterin’s scalability trilemma viewed through a state-change-based classification for common consensus algorithms. Paper presented at the 2020 10th Annual Computing and Communication Workshop and Conference (CCWC), 6–8 January

  44. Halpin H (2020) Deconstructing the decentralization trilemma. arXiv Prep

  45. Pop C, Cioara T, Antal M, Anghel I, Salomie I, Bertoncini M (2018) Blockchain based decentralized management of demand response programs in smart energy grids. Sensors 18(1):162

    Article  Google Scholar 

  46. Decker C, Wattenhofer R (2013) Information propagation in the bitcoin network. Paper presented at the IEEE P2P 2013 Proceedings, 9–11 September

  47. Foytik P, Shetty S, Gochhayat SP, Herath E, Tosh D, Njilla L (2020) A blockchain simulator for evaluating consensus algorithms in diverse networking environments. Paper presented at the 2020 Spring Simulation Conference (SpringSim), 18–20 May

  48. Smetanin S, Ometov A, Komarov M, Masek P, Koucheryavy Y (2020) Blockchain evaluation approaches: State-of-the-art and future perspective. Sensors 20(12):3358

    Article  Google Scholar 

  49. Lathif MRA Nasirifard P, Jacobsen HA (2018) CIDDS: a configurable and distributed DAG-based distributed ledger simulation framework. A Paper presented Proceedings of the 19th International Middleware Conference (Posters), 10–14 December

  50. Stoykov L, Zhang K, Jacobsen HA (2017) Vibes: fast blockchain simulations for large-scale peer-to-peer networks. A Paper presented in Proceedings of the 18th ACM/IFIP/USENIX Middleware Conference: Posters and Demos, 11–15 December

  51. Agard DB, Shackleford MW (2002) A new look at the probabilities in bingo. The Coll Math J 33(4):301–305

    Article  Google Scholar 

  52. Wang Z, Dong X, Li Y, Fang L, Chen P (2017) IoT security model and performance evaluation: a blockchain approach. Paper presented In the 2018 international conference on network infrastructure and digital content (IC-NIDC), 22–24 August

  53. Figueroa-Lorenzo S, Añorga J, Arrizabalaga S (2021) Methodological performance analysis applied to a novel IIoT access control system based on permissioned blockchain. Inf Process Manag 58(4):102558

  54. Nasir Q, Qasse IA, Abu Talib M, Nassif AB (2018) Performance analysis of hyperledger fabric platforms. Secur Commun Netw 1–14

  55. Yasaweerasinghelage R, Staples M, Weber I (2017) Predicting latency of blockchain-based systems using architectural modelling and simulation. A Paper presented in 2017 IEEE International Conference on Software Architecture (ICSA), 3–7 April

  56. Huang D, Ma X, Zhang S (2019) Performance analysis of the raft consensus algorithm for private blockchains. IEEE Trans Syst Man Cybern Syst 50(1):172–181

  57. Alharby M, Van Moorsel A (2020) Blocksim: an extensible simulation tool for blockchain systems. Frontiers Blockchain 3:28

  58. Sukhwani H, Martínez JM, Chang X, Trivedi KS, Rindos A (2017) Performance modeling of PBFT consensus process for permissioned blockchain network (hyperledger fabric). A Paper presented in 2017 IEEE 36th Symposium on Reliable Distributed Systems (SRDS), 26–29 September

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Authors and Affiliations

  1. School of Information and Software Engineering, University of Electronic Science and Technology of China, Street, Chengdu, Sichuan, China

    Melak Ayenew, Hang Lei, Xiaoyu Li, Qian Weizhong, Wenjia Xiang & Abebe Tegene

  2. Center of Artificial Intelligence, Addis Ababa Science and Technology University, Addis Ababa, 16417, Ethiopia

    Melak Ayenew

  3. Mathematics, Kotebe Education University, Addis Ababa, Ethiopia

    Eyerusalem Abeje

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  1. Melak Ayenew
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  2. Hang Lei
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Correspondence to Melak Ayenew.

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Ayenew, M., Lei, H., Li, X. et al. Enhancing the performance of permissionless blockchain networks through randomized message-based consensus algorithm. Peer-to-Peer Netw. Appl. 16, 499–519 (2023). https://doi.org/10.1007/s12083-022-01407-3

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