01-30, 15:20–15:40 (Europe/Zurich), Beacon Stage
We present Mahi-Mahi, the first asynchronous BFT consensus protocol that achieves sub-second latency in the WAN while processing over 100,000 transactions per second. We accomplish this remarkable performance by building Mahi-Mahi on an uncertified structured Directed Acyclic Graph (DAG). By forgoing explicit certification, we significantly reduce the number of messages required to commit and minimize CPU overhead associated with certificate verification. Mahi-Mahi introduces a novel commit rule that allows committing multiple blocks in each DAG round, while ensuring liveness in the presence of an asynchronous adversary. Mahi-Mahi can be parametrized to either attempt to commit within 5 message delays, maximizing the probability of commitment under a continuously active asynchronous adversary, or within 4 message delays, which reduces latency under a more moderate and realistic asynchronous adversary. We demonstrate the safety and liveness of Mahi-Mahi in a Byzantine context. Subsequently, we evaluate Mahi-Mahi in a geo-replicated setting and compare its performance against state-of-the-art asynchronous consensus protocols, showcasing Mahi-Mahi's significantly lower latency.
Paper Link: https://arxiv.org/abs/2410.08670
This paper is a joint work between EPFL, Mysten Labs, UCL, and Alan Turing institute.
As I discussed with "Benjamin Kraner", this paper is currently under submission in a double blind conference, and therefore we kindly request you to not include the paper in the standard conference proceedings.
However, you are free to use presentation topic, speaker details in the web / twitter or any other platform, without any limit. For more information please contact [email protected]
The paper link: https://arxiv.org/abs/2410.08670
I will present the content of this paper, and propose a few improvements too.
I am a distributed systems engineer and researcher. I completed my Computer Science degree at the University of Moratuwa, Sri Lanka, where I began my early research on neural machine translation for low-resourced languages. I then pursued a Master's degree at the same university, focusing on distributed and cloud computing. During my Master's, I worked on load balancing, microservices performance characterization, and server architectures.
In 2019, I started my PhD at EPFL, Lausanne, Switzerland, where I focus on robust and resilient consensus protocols. My work involves designing new consensus protocols, implementing them, and conducting extensive evaluations in real-world setups.