Dynamical coupling outperforms “majority wins” in organizing redundancy to mitigate noise

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Inclusion of redundancy has been one of the primary techniques to reduce the probability of error and to achieve reliability in computing systems and many other engineered systems. Rather than using one system, a group of identical systems is typically used and the final output is determined based on the collective outputs of the redundant systems. A very common technique to obtain an output from a redundant set of systems is “majority wins” (MW) where the majority result is assumed to be the final output. Recently we have shown that the dynamical coupling (DC) of redundant, identical systems reduces local noise. In this approach, redundant systems actively and dynamically collaborate to reduce their combined noise level. Here we present a comparison between MW and DC and demonstrate that a well-designed, optimized DC has better performance in reducing error. In this paper, we mostly focus on noise in computing systems and study redundancy and MW and DC in this context. However, the results can be applied to other similar applications, such as data sensing, oscillators, etc. DC can be implemented with minimal overhead or extra computational complexity, which makes it a suitable mechanism for organizing redundancy to achieve noise robustness.


dynamics, coupling, noise, chaos

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