Speeding Dumbo: Making Asynchronous (Permissioned) Consensus Even Faster

Speeding Dumbo: Making Asynchronous (Permissioned) Consensus Even Faster

Cybersecurity Seminars Online seminar
Thursday, 10 February 2022
2 pm - 3 pm (AEDT)
Free

Asynchronous BFT consensus protocols can enable a set of honest parties to reach agreement on an ever-growing linearized log of transactions, despite arbitrary communication delay. Such asynchronous protocols are arguably the most robust candidates to implement permissioned blockchains deployed over the fluctuating global Internet. However, they suffer from suboptimal performance, despite recent progress on the topic. In particular, there exists a serious practicality hurdle due to large confirmation latency, because the existing designs have to interact for several dozens of rounds to output each block. This talk will dissect the efficiency bottlenecks of the prior art and then present Speeding-Dumbo, a very recent design that can reduce the expected round complexity of asynchronous BFT consensus to about a dozen of rounds (at worst case). The reduced round complexity together with other optimizations can gain great performance improvement in the real-world WAN environment, e.g., realize a confirmation latency that is only about half of Dumbo BFT (CCS'20).

Based on the following work:
[GLL+22] Bingyong Guo, Yuan Lu, Zhenliang Lu, Qiang Tang, Jing Xu, Zhenfeng Zhang. ‘Speeding Dumbo: Pushing Asynchronous BFT Closer to Practice’. to appear in NDSS, 2022.

About the speaker

Yuan Lu
Faculty member, Institute of Software Chinese Academy of Sciences

Dr. Yuan Lu is currently a faculty member and blockchain researcher at the Institute of Software, Chinese Academy of Sciences. His main research areas are blockchain consensus and decentralized applications, in particular, making them secure yet efficient. Many of his recent studies, such as Dumbo consensus protocols, appeared at flagship venues of security and distributed computing. He received his PhD degree with best thesis award from New Jersey Institute of Technology USA and Bachelor of Science degree from Nankai University China. His research was generously supported by NSF of China, MOST of China, JD.com, and Chinese Academy of Sciences.

Monash University values the privacy of every individual's personal information and is committed to the protection of that information from unauthorised use and disclosure except where permitted by law. For information about the handling of your personal information please see Data Protection and Privacy Procedure and the relevant Data Protection and Privacy Collection Statement that applies to you depending on the nature of your interaction with us.

If you have any questions about how Monash University is collecting and handling your personal information, please contact our Data Protection and Privacy Office at dataprotectionofficer@monash.edu.

Research

Event contact

Share this event