Low powered blockchain consensus protocols based on consistent hash

  • Lei YuEmail author
  • Xiao-fang Zhao
  • Yan Jin
  • Heng-yi Cai
  • Bo Wei
  • Bin Hu


Current blockchain consensus protocols have a triangle of contradictions in aspects of decentralization, security, and energy consumption, and cannot be synchronously optimized. We describe a design of two new blockchain consensus protocols, called “CHB-consensus” and “CHBD-consensus,” based on a consistent hash algorithm. Honest miners can fairly gain the opportunity to create blocks. They do not consume any extra computational power resources when creating new blocks, and such blocks can obtain the whole blockchain network to confirm consensus with fairness. However, malicious miners have to pay massive computational power resources for attacking the new block creation privilege or double-spending. Blockchain networks formed by CHB-consensus and CHBD-consensus are based on the same security assumption as that in Bitcoin systems, so they save a huge amount of power without sacrificing decentralization or security. We analyze possible attacks and give a rigorous but adjustable validation strategy. CHB-consensus and CHBD-consensus introduce a certification authority (CA) system, which does not have special management or control rights over blockchain networks or data structures, but carries the risk of privacy breaches depending on credibility and reliability of the CA system. Here, we analyze the robustness and energy consumption of CHB-consensus and CHBD-consensus, and demonstrate their advantages through theoretical derivation.

Key words

Blockchain Consensus protocol Consistent hash Low energy consumption Decentralization 

CLC number



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Compliance with ethics guidelines

Lei YU, Xiao-fang ZHAO, Yan JIN, Heng-yi CAI, Bo WEI, and Bin HU declare that they have no conflict of interest.


  1. Asolo B, 2018. Delegated proof-of-stake (DPoS) explained. Google Scholar
  2. Back A, 2002. Hashcash—a denial of service counter-measure. Google Scholar
  3. Bahri L, Girdzijauskas S, 2018. When trust saves energy: a reference framework for proof of trust (PoT) blockchains. Companion Proc Web Conf, p.1165–1169. Google Scholar
  4. Castro M, Liskov B, 1999. Practical Byzantine fault tolerance. Proc 3rd Symp on Operating Systems Design and Implementation, p.173–186.Google Scholar
  5. Douceur JR, 2002. The Sybil attack. In: Druschel P, Kaashoek F, Rowstron A (Eds.), Peer-to-Peer Systems. Springer Berlin Heidelberg, p.251–260.zbMATHGoogle Scholar
  6. Dwork C, Naor M, 1992. Pricing via processing or combatting junk mail. Proc 12th Annual Int Cryptology Conf on Advances in Cryptology, p.139–147. zbMATHGoogle Scholar
  7. Fan J, Yi LT, Shu JW, 2013. Research on the technologies of Byzantine system. J Softw, 24(6):1346–1360 (in Chinese).CrossRefGoogle Scholar
  8. Fedotova N, Veltri L, 2006. Byzantine generals problem in the light of P2P computing. Proc 3rd Annual Int Conf on Mobile and Ubiquitous Systems: Networking & Services, p.1–5. Google Scholar
  9. Giungato P, Rana R, Tarabella A, et al., 2017. Current trends in sustainability of Bitcoins and related blockchain technology. Sustainability, 9(12), Article 2214.
  10. Karger D, Lehman E, Leighton T, et al., 1997. Consistent hashing and random trees: distributed caching protocols for relieving hot spots on the World Wide Web. Proc 29th Annual ACM Symp on Theory of Computing, p.654–663. zbMATHGoogle Scholar
  11. King S, Nadal S, 2012. PPCoin: peer-to-peer crypto-currency with proof-of-stake. Google Scholar
  12. Lamport L, 1983. The weak Byzantine generals problem. J ACM, 30(3):668–676. MathSciNetCrossRefGoogle Scholar
  13. Lamport L, Shostak R, Pease M, 1982. The Byzantine generals problem. ACM Trans Programm Lang Syst, 4(3):382–401.CrossRefGoogle Scholar
  14. Milutinovic M, He W, Wu H, et al., 2016. Proof of luck: an efficient blockchain consensus protocol. Proc 1st Workshop on System Software for Trusted Execution, p.1–6. Google Scholar
  15. Mishra SP, Jacob V, Radhakrishnan S, 2017. Energy consumption—Bitcoin’s Achilles heel. Google Scholar
  16. Nakamoto S, 2008. Bitcoin: a peer-to-peer electronic cash system. Google Scholar
  17. O’ Dwyer KJ, Malone D, 2014. Bitcoin mining and its energy footprint. Proc 25th IET Irish Signals & Systems Conf and China-Ireland Int Conf on Information and Communications Technologies, p.280-285. Google Scholar
  18. Reischuk R, 1985. A new solution for the Byzantine generals problem. Inform Contr, 64(1-3):23–42. MathSciNetCrossRefGoogle Scholar
  19. Vranken H, 2017. Sustainability of Bitcoin and blockchains. Curr Opin Environ Sustain, 28:1–9. CrossRefGoogle Scholar
  20. Yuan Y, Wang FY, 2016. Blockchain: the state of the art and future trends. Acta Autom Sin, 42(4):481–494 (in Chinese). Google Scholar

Copyright information

© Zhejiang University and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.University of Chinese Academy of SciencesBeijingChina
  2. 2.Institute of Computing TechnologyChinese Academy of SciencesBeijingChina

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