Lessons from HotStuff

Autor: Malkhi, Dahlia, Yin, Maofan
Rok vydání: 2023
Předmět:
Druh dokumentu: Working Paper
Popis: This article will take you on a journey to the core of blockchains, their Byzantine consensus engine, where HotStuff emerged as a new algorithmic foundation for the classical Byzantine generals consensus problem. The first part of the article underscores the theoretical advances HotStuff enabled, including several models in which HotStuff-based solutions closed problems which were opened for decades. The second part focuses on HotStuff performance in real life setting, where its simplicity drove adoption of HotStuff as the golden standard for blockchain design, and many variants and improvements built on top of it. Both parts of this document are meant to describe lessons drawn from HotStuff as well as dispel certain myths.
Databáze: arXiv