Description
TL;DR: A mathematical weight-design method that can converge substantially faster than optimized symmetric updates in selected network topologies.
About This Document
He Hao and Prabir Barooah analyze distributed averaging algorithms whose nodes repeatedly combine neighboring states. They prove size-independent convergence behavior for certain lattice graphs under asymmetric weighting and use a Sturm–Liouville continuum approximation to design weights for broader graph families, supported by numerical comparisons.
Why Bitcoin People May Care
This is not Bitcoin or blockchain consensus. It studies cooperative numerical averaging, not adversarial transaction ordering in a permissionless network. Bitcoin readers may still care because graph topology and information flow shape every decentralized protocol. The speed results depend on the paper's linear model, graph assumptions, and designed weights rather than proof of work.
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Document Details
- Title: Faster Distributed Consensus with Asymmetric Weights
- Author / organization: He Hao and Prabir Barooah
- Year: 2012
- Language: English
- Document type: Distributed-consensus research paper
- Pages: 23
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