An empirical perspective on causal consistency

Alejandro Tomsic 1, 2 Tyler Crain 1, 2 Marc Shapiro 1, 2
2 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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Communication dans un congrès
W. on Principles and Practice of Consistency for Distributed Data (PaPoC), Apr 2015, Bordeaux, France. ACM, W. on Principles and Practice of Consistency for Distributed Data (PaPoC), pp.2:1--2:3, 2015, 〈http://eurosys2015.labri.fr/〉. 〈10.1145/2745947.2745949〉
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Dernière modification le : vendredi 31 août 2018 - 09:25:54
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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), Apr 2015, Bordeaux, France. ACM, W. on Principles and Practice of Consistency for Distributed Data (PaPoC), pp.2:1--2:3, 2015, 〈http://eurosys2015.labri.fr/〉. 〈10.1145/2745947.2745949〉. 〈hal-01218208〉

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