The third part of the series deals with the more advanced Consensus protocols introduced by the whitepaper called “Snowflake” and “Snowball”, and in particular their mechanisms to finalize a consensus decision of nodes. Further, we will outline a weakness in these mechanisms and propose a change (“Blizzard”) that resolves it.

In the second part of the series we take a look at the most basic Snow protocol, called “Slush”. We outline how this protocol works, including the effects of various network and tuning parameters on its performance, and give a rough sketch of our approach to analyze this protocol.

In this three part series, we look at the “Snow” protocols that address the fundamental consensus problem and were introduced in a whitepaper by a group associated with AvaLabs that pioneered the Avalanche blockchain infrastructure. This first part gives an overview of these Snow protocols and a summary of our findings.

We introduce a new abstraction for expressing fault-tolerant consensus protocols in open, permissionless networks. It generalizes fail-prone systems and Byzantine quorum systems, asymmetric distributed trust, and gives a new characterization of the model used in the Stellar blockchain.

A new, efficient protocol prevents attacks on decentralized finance platforms and ensures a novel notion of differential order-fairness for transactions in atomic broadcast.

Composing Byzantine quorum systems for securing distributed protocols

Among asynchronous, randomized, and signature-free implementations of consensus, the protocols by Mostéfaoui et al. (PODC 2014 and JACM 2015) represent a landmark result.

We show how to realize randomized signature-free asynchronous Byzantine consensus with asymmetric quorum systems.

Scaling blockchains by reducing the concurrency across token transactions.

A technical analysis of Ripple’s protocol reveals that it ensures neither safety nor liveness under the stated assumptions.

How does one express a trust structure for consensus in a distributed system that does more than counting possible faults?

A sound model for blockchain consensus with flexible and subjective trust.

Blog posts here can be longer than tweets and are still easier to read than research papers.