Breaking the Scalability Barrier of Causal Broadcast for Large and Dynamic Systems - Inria - Institut national de recherche en sciences et technologies du numérique
Pré-Publication, Document De Travail Année : 2018

Breaking the Scalability Barrier of Causal Broadcast for Large and Dynamic Systems

Résumé

Many distributed protocols and applications rely on causal broadcast to ensure consistency criteria. However, none of causality tracking state-of-the-art approaches scale in large and dynamic systems. This paper presents a new non-blocking causal broadcast protocol suited for dynamic systems. The proposed protocol outperforms state-of-the-art in size of messages, execution time complexity, and local space complexity. Most importantly, messages piggyback control information the size of which is constant. We prove that for both static and dynamic systems. Consequently, large and dynamic systems can finally afford causal broadcast .
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Dates et versions

hal-01778901 , version 1 (26-04-2018)
hal-01778901 , version 2 (15-11-2018)

Identifiants

  • HAL Id : hal-01778901 , version 1

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Brice Nédelec, Pascal Molli, Achour Mostefaoui. Breaking the Scalability Barrier of Causal Broadcast for Large and Dynamic Systems. 2018. ⟨hal-01778901v1⟩
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