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A Weaker Knowledge Connectivity Condition Sufficient for Fault-Tolerant Consensus with Unknown Participants

Authors: Jichiang Tsai 0001; Che-Cheng Chang;

A Weaker Knowledge Connectivity Condition Sufficient for Fault-Tolerant Consensus with Unknown Participants

Abstract

The agreement problem is usually exploited to improve the fault-tolerant capability of software systems. For self-organized networks like cloud computing architectures that possess highly decentralized and self-organized natures, consensus, which is essential to solving the agreement problem, in such networks cannot be achieved in the ways for traditional fixed networks. To address this problem of Consensus with Unknown Participants (CUP), a variant of the traditional consensus problem was proposed in the literature. Correspondingly, the CUP problem considering process crashes was also introduced, called the Fault-Tolerant Consensus with Unknown Participants (FT-CUP) problem. In this paper, we propose a new knowledge connectivity condition sufficient for solving the FT-CUP problem. Our new condition is weaker and more viable than an existing one, which is hard to implement in practice.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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