In this article we investigate randomized binary majority consensus in networks with random topologies and noise. Using computer simulations, we show that asynchronous Simple Majority rule can reach ≃ 100% convergence rate being randomized by an update-biased random neighbor selection and a small fraction of errors. Next, we show that such gains are robust towards additive noise and topology randomization.
Efficient binary consensus in randomized and noisy environments
MARCENARO, LUCIO
2014-01-01
Abstract
In this article we investigate randomized binary majority consensus in networks with random topologies and noise. Using computer simulations, we show that asynchronous Simple Majority rule can reach ≃ 100% convergence rate being randomized by an update-biased random neighbor selection and a small fraction of errors. Next, we show that such gains are robust towards additive noise and topology randomization.
File in questo prodotto:
Non ci sono file associati a questo prodotto.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
