Cover Image for FTF Consensus Ep4 - Pipes Model
Cover Image for FTF Consensus Ep4 - Pipes Model
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FTF Consensus Ep4 - Pipes Model

Hosted by Samuel Laferriere
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Karthik Nayak will be presenting his paper "The Pipes Model for Latency and Throughput Analysis", co-authored with Andrew Lewis-Pye and Nibesh Shrestha.

Protocols for State-Machine-Replication (sometimes called blockchain' protocols) generally make use of rotating leaders to drive consensus. In typical protocols (henceforth called single-sender' protocols), the leader is a single processor responsible for making and disseminating proposals to others. Since the leader acts as a bottleneck, apparently limiting throughput, a recent line of research has investigated the use of `multi-sender' protocols in which many processors distribute proposals in parallel. Examples include DAG-based protocols such as DAG-Rider, Bullshark, Sailfish, Cordial Miners, Mysticeti, and variants such as Autobahn. However, existing models do not allow for a formal analysis to determine whether these protocols can actually handle higher throughputs than single-sender protocols such as PBFT, Tendermint, and HotStuff.\ In this talk, I’ll discuss recent work in which we describe a very simple model that allows for such an analysis. For any given protocol, the model allows one to calculate latency as a function of network bandwidth, network delays, the number of processors $n$, and the incoming transaction rate. Each protocol has a latency bottleneck: an incoming transaction rate at which latency becomes unbounded over the protocol execution, i.e., a maximum throughput that the protocol can handle without unbounded latency. If one compares single-sender protocols that use pipelining and erasure coding, such as DispersedSimplex, with DAG-based protocols such as Sailfish or Bullshark, the former are seen to have lower latency for a wide range of throughputs, while the benefit of the latter protocols is that they have a latency bottleneck (max throughput) which is higher by a constant factor.

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