Byzantine-tolerant uniform node sampling service in large-scale networks

We consider the problem of achieving uniform node sampling in large scale systems in presence of Byzantine nodes. This service offers a single simple primitive that returns, upon invocation, the identifier of a random node that belongs to the system. We first propose an omniscient strategy that proc...

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Vydáno v:International journal of parallel, emergent and distributed systems Ročník 36; číslo 5; s. 412 - 439
Hlavní autoři: Anceaume, Emmanuelle, Busnel, Yann, Sericola, Bruno
Médium: Journal Article
Jazyk:angličtina
Vydáno: Abingdon Taylor & Francis 03.09.2021
Taylor & Francis Ltd
Témata:
Byzantine nodes
Computer Science
Data stream
Data Structures and Algorithms
Distributed, Parallel, and Cluster Computing
Information Theory
Markov chains
Nodes
randomised approximation algorithm
Sampling
uniform sampling
Randomized approximation algorithm
Markov chains
Data stream
Byzantine nodes
Uniform sampling
ISSN:1744-5760, 1744-5779
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Shrnutí:We consider the problem of achieving uniform node sampling in large scale systems in presence of Byzantine nodes. This service offers a single simple primitive that returns, upon invocation, the identifier of a random node that belongs to the system. We first propose an omniscient strategy that processes on the fly an unbounded and arbitrarily biased input stream made of node identifiers exchanged within the system, and outputs a stream that preserves the uniformity property (same probability to appear in the sample). We show that this property holds despite any arbitrary bias introduced by the adversary. We then propose a strategy that is capable of approximating the omniscient strategy without requiring any prior knowledge on the composition of the input stream. We show through both theoretical analysis and extensive simulations that this strategy accurately approximates the omniscient one. We evaluate the resilience of the strategy by studying two representative attacks. We quantify the minimum number of identifiers that Byzantine nodes must insert in the input stream to prevent uniformity. Finally, we propose a new construction in series that allows to both increase the accuracy of a single sketch and decrease the time to converge to a uniform output stream.
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ISSN:1744-5760
1744-5779
DOI:10.1080/17445760.2021.1939873