Scalable Agreement is What We Need

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By Mahnush Movahedi, senior research scientist, Dfinity

6:30 arrive, register, pizza, network
7:00 ACM intro
7:10 Presentation
Live stream at Join us for live streaming at:
https://www.youtube.com/watch?v=xdEa74WcYXI

Abstract:
Fast rise of decentralized systems and cloud computing introduces a new challenge, designing highly scalable algorithms; algorithms that have asymptotically-small communication, computation, and latency costs with respect to the network size. Moreover, systems with thousands or even millions of parties distributed throughout the world which are not controlled by a single trusted authority are likely in danger of faults from untrusted parties. In this talk, we study Dfinity consensus protocol as a scalable method to reach agreement in large decentralized systems.

Throughout this talk, we first look into the Byzantine agreement (BA) problem and study the early protocols for solving this problem and achieving consensus. We then look into lower bounds on BA protocols in a different network and adversarial models to build background knowledge of what is possible and what is not possible to achieve. Then, we study the importance of randomness in designing a BA protocol. We learn how to create global randomness from proof of work and solve the consensus problem in the synchronous model using blockchain. Next, we explore the new technique that combines classical BA protocols with blockchain to address one of the most challenging problems in the consensus domain: scalability. We learn what is a Verifiable Random Function (VRF) and how we can use VRF to create a faster consensus protocol.
Learn more about Dfinity https://dfinity.org/ and its consensus protocol https://arxiv.org/abs/1805.04548

Bio:
Mahnush Movahedi is a senior research scientist at Dfinity working on scalable and fault-tolerant distributed algorithms for consensus, blockchain, and secure computation. Before joining Dfinity and her contribution to its architecture and whitepaper, Mahnush was a Postdoctoral Associate at Yale (2017) and at the University of Virginia (2016). She earned her Ph.D. degree in Computer Science from the University of New Mexico. She published over 30 research papers and was the recipient of multiple awards for her work on secure decentralized systems.