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Practical approximate consensus algorithms for small devices in lossy networks

Published: 25 October 2021 Publication History

Abstract

This paper studies a fundamental distributed primitive - approximate consensus - in connected things using wireless networks. It has been extensively studied in different disciplines, such as fault-tolerant computing, distributed computing, control, and robotics communities. To our surprise, we have not found any practical algorithm that is appropriate for our target scenario - a system of small things that have limited computation and storage capability, and use lossy wireless links to communicate with each other.
This work first identifies the limitations of prior algorithms. Then we present two fault-tolerant approximate consensus algorithms, which minimizes storage complexity. In an n-node system, the first algorithm tolerates crash faults and only needs to store 4 values and an n-bit bit-vector, whereas the second algorithm tolerates up to f Byzantine faults, and needs to store 2f + 4 values and an n-bit bit-vector. In practice, these values are implemented using either integer or float data type. Compared to our algorithms, prior works may need to store O(nD) more values, where D is the number of rounds needed for convergence.

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  1. Practical approximate consensus algorithms for small devices in lossy networks

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    cover image ACM Conferences
    MobiCom '21: Proceedings of the 27th Annual International Conference on Mobile Computing and Networking
    October 2021
    887 pages
    ISBN:9781450383424
    DOI:10.1145/3447993
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    Published: 25 October 2021

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    Author Tags

    1. approximate consensus
    2. fault-tolerance
    3. lossy network

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