What Do We Need to Know to Elect in Networks with Unknown Participants?

Chalopin, Jérémie; Godard, Emmanuel; Naudin, Antoine

doi:10.1007/978-3-319-09620-9_22

Cited by 3 publications

(3 citation statements)

References 15 publications

(24 reference statements)

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“…When this message is delivered by process j, it replies with an ack to i if it has the same knowledge of i (i.e., j belongs to the same component of i). Otherwise, j replies a nack (lines [16][17][18][19][20][21]. It is important to notice that j only replies to i after finishing DISCOVERY.…”

Section: The Sink Protocolmentioning

confidence: 99%

“…After processes discover whether they belong to G sink or not, the processes in the sink execute a standard Byzantine consensus and then, afterwards, send the decision value to non-sink processes. upon Consensus.decide(v) 18) i.decision ← v; 19) ∀j ∈ i.asked, send SET DECISION(i.decision)…”

Section: Achieving Consensusmentioning

confidence: 99%

“…Besides the works summarized in Table 1, there are works studying the FT-CUP problem in a shared memory model [17], or other distributed computing problems such as leader election [18], resource allocation [19] and failure detection [20] when participants are unknown. None of these works consider Byzantine failures.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Knowledge Connectivity Requirements for Solving Byzantine Consensus with Unknown Participants

Alchieri¹,

Bessani²,

Greve³

et al. 2018

IEEE Trans. Dependable and Secure Comput.

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Consensus is a fundamental building block to solve many practical problems that appear on reliable distributed systems. In spite of the fact that consensus is being widely studied in the context of standard networks, few studies have been conducted in order to solve it in dynamic and self-organizing systems characterized by unknown networks. While in a standard network the set of participants is static and known, in an unknown network, such set and number of participants are previously unknown. This work studies the problem of Byzantine Fault-Tolerant Consensus with Unknown Participants, namely BFT-CUP. This new problem aims at solving consensus in unknown networks with the additional requirement that participants in the system may behave maliciously. It presents the necessary and sufficient knowledge connectivity conditions in order to solve BFT-CUP under minimal synchrony requirements. In this way, it proposes algorithms that are shown to be optimal in terms of synchrony and knowledge connectivity among participants in the system.

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