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An empirical perspective on causal consistency

Alejandro Tomsic 1 Tyler Crain 1 Marc Shapiro 1 
1 Regal - Large-Scale Distributed Systems and Applications
LIP6 - Laboratoire d'Informatique de Paris 6, Inria Paris-Rocquencourt
Abstract : Causal consistency is the strongest consistency model under which low-latency and high-availability can be achieved. In the past few years, many causally consistent storage systems have been developed. The long-term goal of this initial work is to perform a deep study and comparison of the different implementations of causal consistency. We identify that protocols that provide causal consistency share the well-known DUR (deferred update replication) algorithmic structure and observe that existing implementations of causal consistency fall into a sub-category of DUR that we name A-DUR (Asynchronous-DUR). In this work, we present the A-DUR algorithmic structure, the pseudocode for the instanti-ation of two causally consistent protocols under the G-DUR framework, and describe the empirical study we intend to perform on causal consistency.
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Submitted on : Tuesday, January 5, 2016 - 7:09:38 PM
Last modification on : Wednesday, September 14, 2022 - 2:42:58 PM
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Alejandro Tomsic, Tyler Crain, Marc Shapiro. An empirical perspective on causal consistency. W. on Principles and Practice of Consistency for Distributed Data (PaPoC), ACM Sigops, Apr 2015, Bordeaux, France. pp.2:1--2:3, ⟨10.1145/2745947.2745949⟩. ⟨hal-01218208⟩



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