pith. sign in

arxiv: 2412.14061 · v2 · pith:52OQJECAnew · submitted 2024-12-18 · 💻 cs.DC

Fast Byzantine Total Order Broadcast

Pith reviewed 2026-05-23 07:13 UTC · model grok-4.3

classification 💻 cs.DC
keywords Byzantine Total Order BroadcastGood-case latencyBinary consensusPartial synchronyLeaderless protocolSignature-freeQuasi-optimal latency
0
0 comments X

The pith

Flutter achieves the first Byzantine total order broadcast with 2Δ + ε good-case latency under synchrony.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper presents Flutter as a Byzantine Total Order Broadcast protocol that delivers messages in 2Δ + ε time units when the network is synchronous and all processes are correct, where Δ is the message delay bound and ε is a small constant. This improves on prior protocols that require at least 3Δ in settings where clients are distinct from servers. A reader would care because reduced latency in fault-tolerant broadcast directly speeds up reliable coordination in distributed systems facing Byzantine faults while preserving determinism and leaderlessness. Flutter builds on a new binary consensus primitive called Blink that decides in Δ time units along its fast path when all correct servers propose the same value. The protocol assumes partial synchrony overall and requires at least 5f + 1 servers.

Core claim

Flutter is the first Byzantine Total Order Broadcast protocol to achieve a broadcast-to-delivery latency of 2Δ + ε time units in the synchronous good case with all processes correct, and the paper proves this latency is quasi-optimal in that no protocol can improve upon it by any finite amount. The construction is deterministic, leaderless, and signature-free. It relies on Blink, a novel binary consensus algorithm with representative validity whose fast path enables decisions in Δ time units precisely when all correct servers propose identical values.

What carries the argument

Blink binary consensus with representative validity, whose fast path decides in Δ when all correct servers propose the same value and thereby enables the overall 2Δ + ε latency bound for total order broadcast.

If this is right

  • The protocol remains correct under partial synchrony outside the good case.
  • It tolerates up to f faults with 5f + 1 servers while staying deterministic and leaderless.
  • Signature freedom implies resilience to quantum attacks on cryptographic primitives.
  • Quasi-optimality means any future protocol cannot reduce good-case latency by a fixed positive amount.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The fast-path structure of Blink could be adapted to other agreement primitives that benefit from quick unanimous decisions.
  • Applications such as state-machine replication might see end-to-end latency reductions when using Flutter as the underlying broadcast layer.
  • Empirical deployment in wide-area networks with measured Δ bounds would test how small ε can be made in practice.

Load-bearing premise

The system must have at least 5f + 1 servers and the network must become synchronous with synchronized clocks whenever all processes are correct.

What would settle it

Run Flutter in a controlled synchronous network with all processes correct and measure whether the observed broadcast-to-delivery latency stays at or below 2Δ + ε; any consistent measurement above that bound would falsify the latency claim.

Figures

Figures reproduced from arXiv: 2412.14061 by Martina Camaioni, Matteo Monti, Pierre-Louis Roman.

Figure 1
Figure 1. Figure 1: Good-case latencies of Flutter and FaB Paxos [72]. Other fast Byzantine Total-Order Broadcast protocols follow FaB Paxos’ leader-based pattern: (1) the client 𝜃 sends its message to the leader 𝜋1, (2) which disseminates it to all servers 𝜋1 . . . 𝜋𝑛, (3) each of which disseminates a confirmation message, (4) upon which all servers decide. These protocols have a good-case latency of 3Δ. Flutter skips the fo… view at source ↗
Figure 2
Figure 2. Figure 2: Blink algorithm. A correct server disseminates its proposal as a suggestion, then proposes to Binary Consensus whichever value it was suggested the most. In the fast path, a correct server decides after receiving (4𝑓 + 1) matching suggestions. In the slow path, a correct server decides whatever Binary Consensus decides. Notation: a correct server’s engagement in Binary Consensus is marked by a crossed bar;… view at source ↗
Figure 3
Figure 3. Figure 3: Example client messages in Flutter, noted 𝑎 to 𝑝, as seen by a correct server at a given time. Messages are organized on a timeline, appearing at the time of their bet. The Consensus status of each message is represented by the two symbols on top of the message: the server’s proposal on top (!to deliver the message, X to reject it), Representative Binary Consensus’s decision on the bottom (!or X to deliver… view at source ↗
Figure 4
Figure 4. Figure 4: Examples of (a) good case and (b) bad case executions of Flutter. Broadcast times are indicated with a question mark; delivery times with an exclamation mark; a correct server’s engagement in Representa￾tive Binary Consensus is marked by a striped bar; proposals and decisions are indicated at the beginning and end of each bar; !represents True; X represents False. Binary Consensus takes longer than one mes… view at source ↗
read the original abstract

This paper presents Flutter, the first Byzantine Total Order Broadcast implementation with a broadcast-to-delivery latency of $2\Delta + \epsilon$ time units, $\Delta$ being the message delay and $\epsilon$ an arbitrarily small constant margin, when all processes are correct, the network is synchronous, hence local clocks are well-synchronized. Under the same conditions, state-of-the-art protocols require at least $3\Delta$ time units in practical deployments where clients differ from servers. We prove Flutter's good-case latency is quasi-optimal, meaning it cannot be improved upon by any finite amount. Flutter is deterministic, leaderless, and signature-free hence quantum-resilient; it assumes partial synchrony and at least $5f + 1$ servers, where $f$ bounds the number of faults. Under the hood, Flutter builds upon Blink, a novel Binary Consensus implementation with Representative Validity, whose fast path enables decisions in $\Delta$ time units when all correct servers propose the same value.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

1 major / 0 minor

Summary. The paper presents Flutter, the first Byzantine Total Order Broadcast implementation with a broadcast-to-delivery latency of 2Δ + ε time units (Δ message delay, ε arbitrarily small) when all processes are correct and the network is synchronous. It requires at least 5f + 1 servers, assumes partial synchrony, and is deterministic, leaderless, and signature-free. The protocol composes instances of a novel Binary Consensus primitive called Blink, whose fast path decides in Δ time units when all correct servers propose the same value. The authors claim to prove the good-case latency bound and that it is quasi-optimal (cannot be improved by any finite amount).

Significance. If the latency bound, quasi-optimality proof, and Blink fast-path correctness hold, the result would advance the state of the art in BFT total-order broadcast by reducing good-case latency below the 3Δ achieved by prior practical protocols (when clients differ from servers). The signature-free and quantum-resilient properties, combined with the explicit higher resilience threshold, are internally consistent with the stated model and could be relevant for latency-sensitive applications under partial synchrony.

major comments (1)
  1. Abstract: the claim that proofs of the latency bound and quasi-optimality are provided cannot be assessed because the text supplies no derivation details, error analysis, or verification steps for the Blink fast path or the 2Δ + ε composition; soundness of the central claims therefore cannot be evaluated from the given material.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their review and the positive assessment of significance. We address the single major comment below and will revise the manuscript accordingly.

read point-by-point responses
  1. Referee: [—] Abstract: the claim that proofs of the latency bound and quasi-optimality are provided cannot be assessed because the text supplies no derivation details, error analysis, or verification steps for the Blink fast path or the 2Δ + ε composition; soundness of the central claims therefore cannot be evaluated from the given material.

    Authors: We agree that the current manuscript does not supply sufficient derivation details, error analysis, or verification steps in the main text, making it difficult to assess soundness from the provided material. The proofs are only sketched at a high level. We will revise by adding detailed derivations for the Blink fast path (including conditions for the Δ decision), explicit error analysis for the ε margin, step-by-step composition to the 2Δ + ε bound, and an expanded quasi-optimality argument with the key lemmas. These will be incorporated into the main body. revision: yes

Circularity Check

0 steps flagged

No significant circularity; new protocol construction is self-contained

full rationale

The paper introduces Flutter and its sub-protocol Blink as novel constructions under explicit assumptions (partial synchrony, 5f+1 resilience). The claimed 2Δ+ε good-case latency and quasi-optimality proof are presented as derived from the protocol rules rather than from any fitted parameters, self-definitional equations, or load-bearing self-citations. No equations, renamings, or reductions to prior author work are visible that would collapse the central result to its inputs by construction. This is the expected outcome for a protocol-design paper whose claims rest on explicit definitions and stated bounds.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 2 invented entities

Review performed on abstract only; full protocol details, proofs, and any additional assumptions are unavailable.

axioms (2)
  • domain assumption Partial synchrony model
    Standard assumption stated for the protocol.
  • domain assumption At least 5f + 1 servers to tolerate f faults
    Explicitly required by the protocol.
invented entities (2)
  • Flutter no independent evidence
    purpose: Byzantine Total Order Broadcast protocol with claimed 2Δ + ε latency
    New protocol introduced in the paper.
  • Blink no independent evidence
    purpose: Binary Consensus with Representative Validity enabling Δ-time decisions on unanimous proposals
    Novel component underlying Flutter's fast path.

pith-pipeline@v0.9.0 · 5691 in / 1360 out tokens · 87403 ms · 2026-05-23T07:13:11.776268+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Reference graph

Works this paper leans on

106 extracted references · 106 canonical work pages

  1. [1]

    Ittai Abraham, Dahlia Malkhi, Kartik Nayak, Ling Ren, and Maofan Yin. 2020. Sync HotStuff: Simple and Practical Synchronous State Machine Replication. In IEEE Symposium on Security and Privacy (SP) . https://doi.org/10.1109/ SP40000.2020.00044

  2. [2]

    Ittai Abraham, Kartik Nayak, Ling Ren, and Zhuolun Xiang. 2021. Good-case Latency of Byzantine Broadcast: a Complete Categorization. In ACM Symposium on Principles of Distributed Computing (PODC) . https://doi.org/10.1145/ 3465084.3467899

  3. [3]

    Ittai Abraham and Gilad Stern. 2021. Information Theoretic HotStuff. In 24th International Conference on Principles of Distributed Systems (OPODIS). https://doi.org/10.4230/LIPIcs.OPODIS.2020.11

  4. [4]

    Aguilera, Naama Ben-David, Rachid Guerraoui, Antoine Murat, Athanasios Xygkis, and Igor Zablotchi

    Marcos K. Aguilera, Naama Ben-David, Rachid Guerraoui, Antoine Murat, Athanasios Xygkis, and Igor Zablotchi

  5. [5]

    Baker, Arash Fayyazi, Sophia Fuhui Lin, Ali Javadi-Abhari, Massoud Pedram, and Frederic T

    uBFT: Microsecond-Scale BFT using Disaggregated Memory. In ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) . https://doi.org/10.1145/3575693.3575732

  6. [6]

    Aguilera, Carole Delporte-Gallet, Hugues Fauconnier, and Sam Toueg

    Marcos K. Aguilera, Carole Delporte-Gallet, Hugues Fauconnier, and Sam Toueg. 2001. Stable Leader Election. In Distributed Computing (DC). https://doi.org/10.1007/3-540-45414-4_8

  7. [7]

    Karolos Antoniadis, Julien Benhaim, Antoine Desjardins, Elias Poroma, Vincent Gramoli, Rachid Guerraoui, Gauthier Voron, and Igor Zablotchi. 2023. Leaderless consensus. Journal of Parallel and Distributed Computing (JPDC) (2023). https://doi.org/10.1016/j.jpdc.2023.01.009

  8. [8]

    Balaji Arun, Sebastiano Peluso, Roberto Palmieri, Giuliano Losa, and Binoy Ravindran. 2017. Speeding up Consensus by Chasing Fast Decisions. In IEEE/IFIP International Conference on Dependable Systems and Networks (DSN) . https: //doi.org/10.1109/DSN.2017.35

  9. [9]

    Pierre-Louis Aublin, Rachid Guerraoui, Nikola Knežević, Vivien Quéma, and Marko Vukolić. 2015. The Next 700 BFT Protocols. ACM Transactions on Computer Systems (TOCS) (2015). https://doi.org/10.1145/2658994

  10. [10]

    Zeta Avarikioti, Lioba Heimbach, Roland Schmid, Laurent Vanbever, Roger Wattenhofer, and Patrick Wintermeyer

  11. [11]

    In International Colloquium on Structural Information and Communication Complexity (SIROCCO)

    FnF-BFT: A BFT protocol with provable performance under attack. In International Colloquium on Structural Information and Communication Complexity (SIROCCO) . https://doi.org/10.1007/978-3-031-32733-9_9

  12. [12]

    Naama Ben-David and Kartik Nayak. 2021. Brief Announcement: Classifying Trusted Hardware via Unidirectional Communication. In ACM Symposium on Principles of Distributed Computing (PODC) . https://doi.org/10.1145/3465084. 3467948

  13. [13]

    Alchieri

    Alysson Bessani, Joao Sousa, and Eduardo E.P. Alchieri. 2014. State Machine Replication for the Masses with BFT-SMaRt. In IEEE/IFIP International Conference on Dependable Systems and Networks (DSN) . https://doi.org/10.1109/DSN.2014.43

  14. [14]

    Francisco Brasileiro, Fabíola Greve, Achour Mostefaoui, and Michel Raynal. 2001. Consensus in One Communication Step. In Parallel Computing Technologies (PaCT). https://doi.org/10.1007/3-540-44743-1_4

  15. [15]

    Christian Cachin, Rachid Guerraoui, and Luís Rodrigues. 2011. Introduction to Reliable and Secure Distributed Program- ming. Springer Science. https://doi.org/10.1007/978-3-642-15260-3

  16. [16]

    Christian Cachin, Klaus Kursawe, and Victor Shoup. 2005. Random Oracles in Constantinople: Practical Asynchronous Byzantine Agreement Using Cryptography. Journal of Cryptology (JCrypt) (2005). https://doi.org/10.1007/s00145- 005-0318-0

  17. [17]

    Christian Cachin and Marko Vukolic. 2017. Blockchain Consensus Protocols in the Wild (Keynote Talk). InInternational Symposium on Distributed Computing (DISC) . https://doi.org/10.4230/LIPIcs.DISC.2017.1

  18. [18]

    Martina Camaioni, Rachid Guerraoui, Matteo Monti, Pierre-Louis Roman, Manuel Vidigueira, and Gauthier Voron

  19. [19]

    In18th USENIX Symposium on Operating Systems Design and Implementation (OSDI)

    Chop Chop: Byzantine Atomic Broadcast to the Network Limit. In18th USENIX Symposium on Operating Systems Design and Implementation (OSDI) . https://www.usenix.org/conference/osdi24/presentation/camaioni

  20. [20]

    Jan Camenisch, Manu Drijvers, Timo Hanke, Yvonne-Anne Pignolet, Victor Shoup, and Dominic Williams. 2022. Internet Computer Consensus. In ACM Symposium on Principles of Distributed Computing (PODC) . https://doi.org/10. 1145/3519270.3538430

  21. [21]

    Miguel Castro and Barbara Liskov. 2002. Practical Byzantine Fault Tolerance and Proactive Recovery.ACM Transactions on Computer Systems (TOCS) (2002). https://doi.org/10.1145/571637.571640

  22. [22]

    Tushar Deepak Chandra and Sam Toueg. 1996. Unreliable Failure Detectors for Reliable Distributed Systems. Journal of the ACM (JACM) (1996). https://doi.org/10.1145/226643.226647

  23. [23]

    Byung-Gon Chun, Petros Maniatis, Scott Shenker, and John Kubiatowicz. 2007. Attested Append-Only Memory: Making Adversaries Stick to their Word. In ACM SIGOPS Symposium on Operating Systems Principles (SOSP) . https: //doi.org/10.1145/1294261.1294280

  24. [24]

    Pierre Civit, Muhammad Ayaz Dzulfikar, Seth Gilbert, Vincent Gramoli, Rachid Guerraoui, Jovan Komatovic, and Manuel Vidigueira. 2022. Byzantine Consensus Is Θ(𝑛2 ): The Dolev-Reischuk Bound Is Tight Even in Partial Synchrony!. In International Symposium on Distributed Computing (DISC) . https://doi.org/10.4230/LIPIcs.DISC.2022.14

  25. [25]

    Pierre Civit, Seth Gilbert, and Vincent Gramoli. 2021. Polygraph: Accountable Byzantine Agreement. In IEEE Interna- tional Conference on Distributed Computing Systems (ICDCS) . https://doi.org/10.1109/ICDCS51616.2021.00046 Fast Leaderless Byzantine Total Order Broadcast 17

  26. [26]

    Pierre Civit, Seth Gilbert, Vincent Gramoli, Rachid Guerraoui, and Jovan Komatovic. 2022. As easy as ABC: Optimal (A)ccountable (B)yzantine (C)onsensus is easy!. In IEEE International Parallel and Distributed Processing Symposium (IPDPS). https://doi.org/10.1109/IPDPS53621.2022.00061

  27. [27]

    Pierre Civit, Seth Gilbert, Rachid Guerraoui, Jovan Komatovic, Matteo Monti, and Manuel Vidigueira. 2023. Every Bit Counts in Consensus. In International Symposium on Distributed Computing (DISC) . https://doi.org/10.4230/LIPIcs. DISC.2023.13

  28. [28]

    Pierre Civit, Seth Gilbert, Rachid Guerraoui, Jovan Komatovic, and Manuel Vidigueira. 2023. On the Validity of Consensus. In ACM Symposium on Principles of Distributed Computing (PODC). https://doi.org/10.1145/3583668.3594567

  29. [29]

    Allen Clement, Edmund Wong, Lorenzo Alvisi, Mike Dahlin, and Mirco Marchetti. 2009. Making Byzantine Fault Tolerant Systems Tolerate Byzantine Faults. In USENIX Symposium on Networked Systems Design and Implementation (NSDI). https://www.usenix.org/conference/nsdi-09/making-byzantine-fault-tolerant-systems-tolerate-byzantine- faults

  30. [30]

    Shir Cohen, Rati Gelashvili, Lefteris Kokoris-Kogias, Zekun Li, Dahlia Malkhi, Alberto Sonnino, and Alexander Spiegelman. 2022. Be Aware of Your Leaders. In Financial Cryptography and Data Security (FC) . https://doi.org/10. 1007/978-3-031-18283-9_13

  31. [31]

    Tyler Crain. 2020. Two More Algorithms for Randomized Signature-Free Asynchronous Binary Byzantine Consensus with 𝑡 < 𝑛/3 and 𝑂 (𝑛2 ) Messages and 𝑂 (1) Round Expected Termination. arXiv:2002.08765 [cs.DC] https: //arxiv.org/abs/2002.08765

  32. [32]

    Tyler Crain, Vincent Gramoli, Mikel Larrea, and Michel Raynal. 2018. DBFT: Efficient Leaderless Byzantine Consensus and its Application to Blockchains. In IEEE International Symposium on Network Computing and Applications (NCA) . https://doi.org/10.1109/NCA.2018.8548057

  33. [33]

    Tyler Crain, Christopher Natoli, and Vincent Gramoli. 2021. Red Belly: A Secure, Fair and Scalable Open Blockchain. In IEEE Symposium on Security and Privacy (SP) . https://doi.org/10.1109/SP40001.2021.00087

  34. [34]

    Flaviu Cristian, Houtan Aghili, Ray Strong, and Danny Dolev. 1995. Atomic Broadcast: From Simple Message Diffusion to Byzantine Agreement. Information and Computation (IC) (1995). https://doi.org/10.1006/inco.1995.1060

  35. [35]

    Philip Daian, Steven Goldfeder, Tyler Kell, Yunqi Li, Xueyuan Zhao, Iddo Bentov, Lorenz Breidenbach, and Ari Juels

  36. [36]

    Pierazzi, F

    Flash Boys 2.0: Frontrunning in Decentralized Exchanges, Miner Extractable Value, and Consensus Instability. In IEEE Symposium on Security and Privacy (SP) . https://doi.org/10.1109/SP40000.2020.00040

  37. [37]

    George Danezis, Lefteris Kokoris-Kogias, Alberto Sonnino, and Alexander Spiegelman. 2022. Narwhal and Tusk: A DAG-Based Mempool and Efficient BFT Consensus. InProceedings of the Seventeenth European Conference on Computer Systems (EuroSys). https://doi.org/10.1145/3492321.3519594

  38. [38]

    Sourav Das, Zhuolun Xiang, and Ling Ren. 2021. Asynchronous Data Dissemination and its Applications. In ACM SIGSAC Conference on Computer and Communications Security (CCS) . https://doi.org/10.1145/3460120.3484808

  39. [39]

    Dan Dobre and Neeraj Suri. 2006. One-step Consensus with Zero-Degradation. In International Conference on Dependable Systems and Networks (DSN) . https://doi.org/10.1109/DSN.2006.55

  40. [40]

    Danny Dolev, Cynthia Dwork, and Larry Stockmeyer. 1987. On the Minimal Synchronism Needed for Distributed Consensus. Journal of the ACM (JACM) (1987). https://doi.org/10.1145/7531.7533

  41. [41]

    Danny Dolev and Rüdiger Reischuk. 1985. Bounds on Information Exchange for Byzantine Agreement. Journal of the ACM (JACM) (1985). https://doi.org/10.1145/2455.214112

  42. [42]

    Dolev and H

    Danny Dolev and H. Raymond Strong. 1983. Authenticated Algorithms for Byzantine Agreement. SIAM J. Comput. (1983). https://doi.org/10.1137/0212045

  43. [43]

    Jiaqing Du, Daniele Sciascia, Sameh Elnikety, Willy Zwaenepoel, and Fernando Pedone. 2014. Clock-RSM: Low-Latency Inter-datacenter State Machine Replication Using Loosely Synchronized Physical Clocks. In IEEE/IFIP International Conference on Dependable Systems and Networks (DSN) . https://doi.org/10.1109/DSN.2014.42

  44. [44]

    Lynch, and Larry J

    Cynthia Dwork, Nancy A. Lynch, and Larry J. Stockmeyer. 1988. Consensus in the presence of partial synchrony. Journal of the ACM (JACM) (1988). https://doi.org/10.1145/42282.42283

  45. [45]

    Vitor Enes, Carlos Baquero, Alexey Gotsman, and Pierre Sutra. 2021. Efficient Replication via Timestamp Stability. In European Conference on Computer Systems (EuroSys) . https://doi.org/10.1145/3447786.3456236

  46. [46]

    Roy Friedman, Achour Mostefaoui, and Michel Raynal. 2005. Simple and Efficient Oracle-Based Consensus Protocols for Asynchronous Byzantine Systems. IEEE Transactions on Dependable and Secure Computing (TDSC) (2005). https: //doi.org/10.1109/TDSC.2005.13

  47. [47]

    Rati Gelashvili, Lefteris Kokoris-Kogias, Alberto Sonnino, Alexander Spiegelman, and Zhuolun Xiang. 2022. Jolteon and Ditto: Network-Adaptive Efficient Consensus with Asynchronous Fallback. InFinancial Cryptography and Data Security (FC). https://doi.org/10.1007/978-3-031-18283-9_14

  48. [48]

    Yossi Gilad, Rotem Hemo, Silvio Micali, Georgios Vlachos, and Nickolai Zeldovich. 2017. Algorand: Scaling Byzantine Agreements for Cryptocurrencies. In ACM Symposium on Operating Systems Principles (SOSP) . https://doi.org/10. 1145/3132747.3132757 18 Matteo Monti, Martina Camaioni, and Pierre-Louis Roman

  49. [49]

    Giacomo Giuliari, Alberto Sonnino, Marc Frei, Fabio Streun, Lefteris Kokoris-Kogias, and Adrian Perrig. 2024. An Empirical Study of Consensus Protocols’ DoS Resilience. InProceedings of the 19th ACM Asia Conference on Computer and Communications Security (ASIA CCS) . https://doi.org/10.1145/3634737.3656997

  50. [50]

    Guy Golan Gueta, Ittai Abraham, Shelly Grossman, Dahlia Malkhi, Benny Pinkas, Michael Reiter, Dragos-Adrian Seredinschi, Orr Tamir, and Alin Tomescu. 2019. SBFT: A Scalable and Decentralized Trust Infrastructure. In IEEE/IFIP International Conference on Dependable Systems and Networks (DSN) . https://doi.org/10.1109/DSN.2019.00063

  51. [51]

    Kexin Hu, Zhenfeng Zhang, Kaiwen Guo, Weiyu Jiang, Xiaoman Li, and Jiang Han. 2023. An optimisation for a two-round good-case latency protocol. IET Information Security (2023). https://doi.org/10.1049/ise2.12123

  52. [52]

    Zsolt István, David Sidler, Gustavo Alonso, and Marko Vukolic. 2016. Consensus in a Box: Inexpensive Coordination in Hardware. In USENIX Symposium on Networked Systems Design and Implementation (NSDI) . https://www.usenix. org/conference/nsdi16/technical-sessions/presentation/istvan

  53. [53]

    Jalalzai, Chen Feng, and Victoria Lemieux

    Mohammad M. Jalalzai, Chen Feng, and Victoria Lemieux. 2024. VBFT: Veloce Byzantine Fault Tolerant Consensus for Blockchains. arXiv:2310.09663 [cs.DC] https://arxiv.org/abs/2310.09663

  54. [54]

    Rüdiger Kapitza, Johannes Behl, Christian Cachin, Tobias Distler, Simon Kuhnle, Seyed Vahid Mohammadi, Wolfgang Schröder-Preikschat, and Klaus Stengel. 2012. CheapBFT: Resource-Efficient Byzantine Fault Tolerance. In ACM European Conference on Computer Systems (EuroSys) . https://doi.org/10.1145/2168836.2168866

  55. [55]

    Idit Keidar and Sergio Rajsbaum. 2001. On the Cost of Fault-Tolerant Consensus When There Are No Faults – A Tutorial. Technical Report MIT-LCS-TR-821

  56. [56]

    Mahimna Kelkar, Fan Zhang, Steven Goldfeder, and Ari Juels. 2020. Order-Fairness for Byzantine Consensus. In Advances in Cryptology – CRYPTO . https://doi.org/10.1007/978-3-030-56877-1_16

  57. [57]

    Marios Kogias and Edouard Bugnion. 2020. HovercRaft: Achieving Scalability and Fault-Tolerance for Microsecond- Scale Datacenter Services. In European Conference on Computer Systems (EuroSys) . https://doi.org/10.1145/3342195. 3387545

  58. [58]

    Ramakrishna Kotla, Lorenzo Alvisi, Mike Dahlin, Allen Clement, and Edmund Wong. 2007. Zyzzyva: Speculative Byzantine Fault Tolerance. In ACM SIGOPS Symposium on Operating Systems Principles (SOSP) . https://doi.org/10. 1145/1294261.1294267

  59. [59]

    Klaus Kursawe. 2002. Optimistic Byzantine agreement. In IEEE Symposium on Reliable Distributed Systems (SRDS) . https://doi.org/10.1109/RELDIS.2002.1180196

  60. [60]

    Petr Kuznetsov, Andrei Tonkikh, and Yan X Zhang. 2021. Revisiting Optimal Resilience of Fast Byzantine Consensus. In ACM Symposium on Principles of Distributed Computing (PODC) . https://doi.org/10.1145/3465084.3467924

  61. [61]

    Aptos Labs. 2022. The Aptos Blockchain: Safe, Scalable, and Upgradeable Web3 Infrastructure. https://github.com/aptos- labs/aptos-core/blob/main/developer-docs-site/static/papers/whitepaper.pdf

  62. [62]

    Leslie Lamport. 1978. Time, Clocks, and the Ordering of Events in a Distributed System. Communications of the ACM (CACM) 21, 7 (1978). https://doi.org/10.1145/359545.359563

  63. [63]

    Leslie Lamport. 2002. Specifying Systems: The TLA+ Language and Tools for Hardware and Software Engineers . Addison- Wesley

  64. [64]

    Leslie Lamport. 2006. Fast Paxos. Distributed Computing (DC) (2006). https://doi.org/10.1007/s00446-006-0005-x

  65. [65]

    Leslie Lamport, Robert Shostak, and Marshall Pease. 1982. The Byzantine Generals Problem. ACM Transactions on Programming Languages and Systems (TOPLAS) 4, 3 (1982). https://doi.org/10.1145/357172.357176

  66. [66]

    Ki Suh Lee, Han Wang, Vishal Shrivastav, and Hakim Weatherspoon. 2016. Globally Synchronized Time via Datacenter Networks. In ACM SIGCOMM Conference (SIGCOMM). https://doi.org/10.1145/2934872.2934885

  67. [67]

    Douceur, Jacob R

    Dave Levin, John R. Douceur, Jacob R. Lorch, and Thomas Moscibroda. 2009. TrInc: Small Trusted Hardware for Large Distributed Systems. In USENIX Symposium on Networked Systems Design and Implementation (NSDI)

  68. [68]

    Lewandowski, J

    W. Lewandowski, J. Azoubib, and W.J. Klepczynski. 1999. GPS: Primary tool for time transfer. Proc. IEEE (1999). https://doi.org/10.1109/5.736348

  69. [69]

    Andrew Lewis-Pye. 2022. Quadratic worst-case message complexity for State Machine Replication in the partial synchrony model. arXiv:2201.01107 [cs.DC] https://arxiv.org/abs/2201.01107

  70. [70]

    Yuliang Li, Gautam Kumar, Hema Hariharan, Hassan Wassel, Peter Hochschild, Dave Platt, Simon Sabato, Minlan Yu, Nandita Dukkipati, Prashant Chandra, and Amin Vahdat. 2020. Sundial: Fault-tolerant Clock Synchronization for Datacenters. In USENIX Symposium on Operating Systems Design and Implementation (OSDI) . https://www.usenix. org/conference/osdi20/pres...

  71. [71]

    Zhuolun Li, Alberto Sonnino, and Philipp Jovanovic. 2023. Performance of EdDSA and BLS Signatures in Committee- Based Consensus. In Workshop on Advanced Tools, Programming Languages, and PLatforms for Implementing and Evaluating Algorithms for Distributed Systems (ApPLIED) . https://doi.org/10.1145/3584684.3597265

  72. [72]

    Karame, and N

    Jian Liu, Wenting Li, Ghassan O. Karame, and N. Asokan. 2019. Scalable Byzantine Consensus via Hardware-Assisted Secret Sharing. IEEE Transactions on Computers (TC) (2019). https://doi.org/10.1109/TC.2018.2860009 Fast Leaderless Byzantine Total Order Broadcast 19

  73. [73]

    Marta Lokhava, Giuliano Losa, David Mazières, Graydon Hoare, Nicolas Barry, Eli Gafni, Jonathan Jove, Rafał Malinowsky, and Jed McCaleb. 2019. Fast and Secure Global Payments with Stellar. In ACM Symposium on Operating Systems Principles (SOSP). https://doi.org/10.1145/3341301.3359636

  74. [74]

    Yuan Lu, Zhenliang Lu, Qiang Tang, and Guiling Wang. 2020. Dumbo-MVBA: Optimal Multi-Valued Validated Asynchronous Byzantine Agreement, Revisited. In ACM Symposium on Principles of Distributed Computing (PODC) . https://doi.org/10.1145/3382734.3405707

  75. [75]

    Junqueira, and Keith Marzullo

    Yanhua Mao, Flavio P. Junqueira, and Keith Marzullo. 2008. Mencius: Building Efficient Replicated State Machines for WANs. In USENIX Symposium on Operating Systems Design and Implementation (OSDI) . https://www.usenix.org/ event/osdi08/tech/full_papers/mao/mao_html

  76. [76]

    Jean-Philippe Martin and Lorenzo Alvisi. 2005. Fast Byzantine consensus. In International Conference on Dependable Systems and Networks (DSN) . https://doi.org/10.1109/DSN.2005.48

  77. [77]

    Andersen, and Michael Kaminsky

    Iulian Moraru, David G. Andersen, and Michael Kaminsky. 2013. There Is More Consensus in Egalitarian Parliaments. In ACM Symposium on Operating Systems Principles (SOSP) . https://doi.org/10.1145/2517349.2517350

  78. [78]

    Achour Mostéfaoui, Hamouma Moumen, and Michel Raynal. 2015. Signature-Free Asynchronous Binary Byzantine Consensus with t < n/3, O(n2) Messages, and O(1) Expected Time. Jounal of the ACM (JACM) (2015). https: //doi.org/10.1145/2785953

  79. [79]

    Achour Mostefaoui and Michel Raynal. 2000. Low cost consensus-based Atomic Broadcast. In Pacific Rim International Symposium on Dependable Computing (PRDC) . https://doi.org/10.1109/PRDC.2000.897283

  80. [80]

    Ali Najafi and Michael Wei. 2022. Graham: Synchronizing Clocks by Leveraging Local Clock Properties. In USENIX Symposium on Networked Systems Design and Implementation (NSDI) . https://www.usenix.org/conference/nsdi22/ presentation/najafi

Showing first 80 references.