A very useful tool in Asynchronus distributed computing is Reliable Broadcast, or simply called Broadcast. It allows a leader to send a message, knowing that all parties will eventually receive the same message, even if a malicious adversary control $f$ parties and $f<n/3$. Broadcast is deterministic and takes just a...| decentralizedthoughts.github.io
In this series of posts, we explore the marvelous world of consensus in the Asynchronous model. In this post, we start by simply defining the problem. Recall the FLP theorem: FLP theorem 1985: Any protocol where no two non-faulty parties decide different values in the asynchronous model that is resilient...| decentralizedthoughts.github.io
After we fix the communication model, synchrony, asynchrony, or partial synchrony, and a threshold adversary we still have 5 important modeling decisions about the adversary power: The type of corruption (passive, crash, omission, or Byzantine). The computational power of the adversary (unbounded, computational, or fine-grained). The adaptivity of the adversary...| decentralizedthoughts.github.io
Verifiable Information Dispersal (or VID) has its roots in the work of Michael Rabin, 1989 which introduced the notion of Information Dispersal (ID). Adding verifiability (referred to as binding in this post) to obtain VIDs was done by Garay, Gennaro, Jutla, and Rabin, 1998 (called SSRI). Cachin and Tessaro, 2004...| decentralizedthoughts.github.io
In the standard distributed computing model, the communication uncertainty is captured by an adversary that can control the message delays. The communication model defines the limits to the power of the adversary to delay messages. There are three basic communication models: the Synchronous model, the Asynchronous model, and the Partial...| decentralizedthoughts.github.io