HotStuff-1: Linear Consensus with One-Phase Speculation
In this talk, I will introduce our recent work, which will be soon presented at SIGMOD 2025. We designed a new BFT consensus protocol, HotStuff-1, that improves the latency of HotStuff-2 by two network-hops while maintaining linear communication complexity against faults. Additionally, HotStuff-1 incorporates an incentive-compatible leader rotation regime that motivates leaders to commit consensus decisions promptly.
HotStuff-1 achieves a reduction by two network hops by sending clients early finality confirmations speculatively, after one phase of the protocol. Unlike previous speculation regimes, the early finality confirmation path of HotStuff-1 is fault-tolerant and the latency improvement does not rely on optimism. We also expose prefix speculation dilemma, an important safety consideration that occurs with leader replacement, and HotStuff-1 is the first protocol that resolves it with linear complexity.
HotStuff-1 embodies an additional mechanism, slotting, that thwarts real-world delays caused by rationally-incentivized leaders. Leaders may also be inclined to sabotage each other’s progress via tail-forking. The slotting mechanism allows leaders to dynamically drive as many decisions as possible allowed by network transmission delays before view timers expire, thus mitigating both threats.
Speaker Biography
Suyash Gupta is an Assistant Professor at the Department of Computer Science, University of Oregon. Prior to joining UO, he received his Ph.D. degree from University of California, Davis and did postdoctoral research as University of California, Berkeley. He also holds two Master of Science degrees: one from Purdue University and other from Indian Institute of Technology Madras. His current research focuses on designing efficient, fault tolerant distributed consensus and communication, and federated learning algorithms. He has also co-authored a book on fault-tolerant distributed transaction processing at Morgan & Claypool. He has been awarded the Best Graduate Researcher Award for 2021 by UC Davis and Best Paper Award at EuroSys’23. He also led the design of Apache ResilientDB, which is incubating under Apache Software Foundation (ASF) and is employed by researchers at UO, UC Davis, UC Berkeley, UC Irvine, UC Santa Barbara, UPenn, McMaster, Umm Al-Qura University and developers at Alibaba, Radix DLT, Mysten Labs, Oracle, Cisco, and AWS. In his free time, Suyash likes to code, and his team won Best Hacker Award at BostonHacks, HackIllinois, and HackPrinceton, among others.
