Comparative Analysis of Classical and Novel Consensus Protocols

Authors

  • Hugo Silva Postdoctoral Researcher, Department of Computer Science, Advanced Computing University, Paris, France, France Author
  • Oscar Silva Senior Lecturer, Department of Machine Learning, Central European Tech University, Vienna, Austria, Austria Author

Keywords:

consensus protocols, blockchain, proof-of-stake, proof-of-work, Byzantine fault tolerance, CPQI, distributed ledger, throughput, finality, decentralisation, France, Austria

Abstract

Picking the right consensus protocol for a blockchain deployment is harder than it looks. Proof-of-Work has been around the longest and provides strong Sybil resistance, but its electricity bill is difficult to justify outside a handful of high-value use cases. Newer alternatives such as Proof-of-Stake, Delegated Proof-of-Stake, PBFT derivatives, and Proof-of-Authority each promise improvements on one front while quietly introducing trade-offs on another. The trouble is that most published comparisons only look at one or two dimensions at a time, so practitioners end up stitching together an incomplete picture. In this study we gathered operational data from 200 real deployments running across labs in Paris and Vienna over a four-year window (2019-2023), covering all five major protocol families. We built a composite score called the Consensus Protocol Quality Index, or CPQI, that rolls up throughput efficiency, fault tolerance depth, energy proportionality, finality assurance, and governance adaptability into one number. The weights came straight from a regression against actual adoption outcomes rather than from expert guesswork. CPQI turned out to be a solid predictor: r = +0.84 against the adoption score and an AUC of 0.883 when classifying surviving versus abandoned deployments. Proof-of-Stake variants came out on top with a mean CPQI of 0.814, while Proof-of-Work sat at 0.588. Barely a third of all deployments cleared the 0.75 mark, which tells us there is plenty of room for the field to do better.

Author Biographies

  • Hugo Silva, Postdoctoral Researcher, Department of Computer Science, Advanced Computing University, Paris, France, France

    Postdoctoral Researcher, Department of Computer Science, Advanced Computing University, Paris, France, France

  • Oscar Silva, Senior Lecturer, Department of Machine Learning, Central European Tech University, Vienna, Austria, Austria

    Senior Lecturer, Department of Machine Learning, Central European Tech University, Vienna, Austria, Austria

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Published

2025-03-15

How to Cite

Comparative Analysis of Classical and Novel Consensus Protocols. (2025). Blockchain, Web3 & Digital Trust Journal P-ISSN 3117-597X and E-ISSN 3117-5988, 2(1), 1-8. https://galaxiauniverse.com/index.php/BWDTJ/article/view/442