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Coracle: Evaluating Consensus at the Internet Edge

Published:17 August 2015Publication History

ABSTRACT

Distributed consensus is fundamental in distributed systems for achieving fault-tolerance. The Paxos algorithm has long dominated this domain, although it has been recently challenged by algorithms such as Raft and Viewstamped Replication Revisited. These algorithms rely on Paxos's original assumptions, unfortunately these assumptions are now at odds with the reality of the modern internet. Our insight is that current consensus algorithms have significant availability issues when deployed outside the well defined context of the datacenter. To illustrate this problem, we developed Coracle, a tool for evaluating distributed consensus algorithms in settings that more accurately represent realistic deployments. We have used Coracle to test two examples of network configurations that contradict the liveness claims of the Raft algorithm. Through the process of exercising these algorithms under more realistic assumptions, we demonstrate wider availability issues faced by consensus algorithms when deployed on real world networks.

References

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      • Published in

        cover image ACM Conferences
        SIGCOMM '15: Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication
        August 2015
        684 pages
        ISBN:9781450335423
        DOI:10.1145/2785956

        Copyright © 2015 Owner/Author

        Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 17 August 2015

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        Acceptance Rates

        SIGCOMM '15 Paper Acceptance Rate40of242submissions,17%Overall Acceptance Rate554of3,547submissions,16%

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