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Pulling multiple nodes for rumor spreading

By Frédérique Robin, Bruno Sericola, Emmanuelle Anceaume and Yves Mocquard


In this paper, we propose and analyze a new asynchronous rumor spreading protocol to deliver a rumor to all the nodes of a large-scale distributed network. This spreading protocol relies on what we call a k-pull operation, with $k ≥ 2$. Specifically during a k-pull operation, an uninformed node i contacts $k − 1$ random nodes in the network, and if at least one of them knows the rumor, then node i learns it. We perform a thorough study of $T k,n ,$ the total number of k-pull operations needed for all the nodes to learn the rumor. We prove that the mean number of interactions needed for all the nodes to be informed is in $O (n ln(n)/(k − 1))$, which generalizes the standard case $k = 2$ for the push-pull, push and pull protocols. We also analyze the tail of $T k,n$ and prove that $T k,n 2$, our new protocol requires less operations than the traditional push-pull or push (resp. pull) protocols by using stochastic dominance arguments

Topics: [INFO]Computer Science [cs], [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC]
Publisher: HAL CCSD
Year: 2020
OAI identifier: oai:HAL:hal-02500504v1
Provided by: HAL-Rennes 1
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