Jolteon and ditto: Network-adaptive efficient consensus with asynchronous fallback
Gelashvili R, Kokoris Kogias E, Sonnino A, Spiegelman A, Xiang Z. 2022. Jolteon and ditto: Network-adaptive efficient consensus with asynchronous fallback. Financial Cryptography and Data Security. FC: Financial Cryptography, LNCS, vol. 13411, 296–315.
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Author
Gelashvili, Rati;
Kokoris Kogias, LefterisISTA;
Sonnino, Alberto;
Spiegelman, Alexander;
Xiang, Zhuolun
Department
Series Title
LNCS
Abstract
Existing committee-based Byzantine state machine replication (SMR) protocols, typically deployed in production blockchains, face a clear trade-off: (1) they either achieve linear communication cost in the steady state, but sacrifice liveness during periods of asynchrony, or (2) they are robust (progress with probability one) but pay quadratic communication cost. We believe this trade-off is unwarranted since existing linear protocols still have asymptotic quadratic cost in the worst case. We design Ditto, a Byzantine SMR protocol that enjoys the best of both worlds: optimal communication on and off the steady state (linear and quadratic, respectively) and progress guarantee under asynchrony and DDoS attacks. We achieve this by replacing the view-synchronization of partially synchronous protocols with an asynchronous fallback mechanism at no extra asymptotic cost. Specifically, we start from HotStuff, a state-of-the-art linear protocol, and gradually build Ditto. As a separate contribution and an intermediate step, we design a 2-chain version of HotStuff, Jolteon, which leverages a quadratic view-change mechanism to reduce the latency of the standard 3-chain HotStuff. We implement and experimentally evaluate all our systems to prove that breaking the robustness-efficiency trade-off is in the realm of practicality.
Publishing Year
Date Published
2022-10-22
Proceedings Title
Financial Cryptography and Data Security
Acknowledgement
We thank our shepherd Aniket Kate and the anonymous reviewers at FC 2022 for their helpful feedback. This work is supported by the Novi team at Facebook. We also thank the Novi Research and Engineering teams for valuable feedback, and in particular Mathieu Baudet, Andrey Chursin, George Danezis, Zekun Li, and Dahlia Malkhi for discussions that shaped this work.
Volume
13411
Page
296-315
Conference
FC: Financial Cryptography
Conference Location
Radisson Grenada Beach Resort, Grenada
Conference Date
2022-05-02 – 2022-05-06
ISBN
ISSN
eISSN
IST-REx-ID
Cite this
Gelashvili R, Kokoris Kogias E, Sonnino A, Spiegelman A, Xiang Z. Jolteon and ditto: Network-adaptive efficient consensus with asynchronous fallback. In: Financial Cryptography and Data Security. Vol 13411. Springer Nature; 2022:296-315. doi:10.1007/978-3-031-18283-9_14
Gelashvili, R., Kokoris Kogias, E., Sonnino, A., Spiegelman, A., & Xiang, Z. (2022). Jolteon and ditto: Network-adaptive efficient consensus with asynchronous fallback. In Financial Cryptography and Data Security (Vol. 13411, pp. 296–315). Radisson Grenada Beach Resort, Grenada: Springer Nature. https://doi.org/10.1007/978-3-031-18283-9_14
Gelashvili, Rati, Eleftherios Kokoris Kogias, Alberto Sonnino, Alexander Spiegelman, and Zhuolun Xiang. “Jolteon and Ditto: Network-Adaptive Efficient Consensus with Asynchronous Fallback.” In Financial Cryptography and Data Security, 13411:296–315. Springer Nature, 2022. https://doi.org/10.1007/978-3-031-18283-9_14.
R. Gelashvili, E. Kokoris Kogias, A. Sonnino, A. Spiegelman, and Z. Xiang, “Jolteon and ditto: Network-adaptive efficient consensus with asynchronous fallback,” in Financial Cryptography and Data Security, Radisson Grenada Beach Resort, Grenada, 2022, vol. 13411, pp. 296–315.
Gelashvili R, Kokoris Kogias E, Sonnino A, Spiegelman A, Xiang Z. 2022. Jolteon and ditto: Network-adaptive efficient consensus with asynchronous fallback. Financial Cryptography and Data Security. FC: Financial Cryptography, LNCS, vol. 13411, 296–315.
Gelashvili, Rati, et al. “Jolteon and Ditto: Network-Adaptive Efficient Consensus with Asynchronous Fallback.” Financial Cryptography and Data Security, vol. 13411, Springer Nature, 2022, pp. 296–315, doi:10.1007/978-3-031-18283-9_14.
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