Reliable communication over highly connected noisy networks

Noga Alon, Mark Braverman, Klim Efremenko, Ran Gelles, Bernhard Haeupler

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

We consider the task of multiparty computation performed over networks in the presence of random noise. Given an n-party protocol that takes R rounds assuming noiseless communication, the goal is to find a coding scheme that takes R rounds and computes the same function with high probability even when the communication is noisy, while maintaining a constant asymptotic rate, i.e., while keeping lim inf n , R R/ R positive. Rajagopalan and Schulman (STOC ’94) were the first to consider this question, and provided a coding scheme with rate O(1 / log (d+ 1)) , where d is the maximal degree in the network. While that scheme provides a constant rate coding for many practical situations, in the worst case, e.g., when the network is a complete graph, the rate is O(1 / log n) , which tends to 0 as n tends to infinity. We revisit this question and provide an efficient coding scheme with a constant rate for the interesting case of fully connected networks. We furthermore extend the result and show that if a (d-regular) network has mixing time m, then there exists an efficient coding scheme with rate O(1 / m3log m). This implies a constant rate coding scheme for any n-party protocol over a d-regular network with a constant mixing time, and in particular for random graphs with n vertices and degrees nΩ ( 1 ).

Original languageEnglish
Pages (from-to)505-515
Number of pages11
JournalDistributed Computing
Volume32
Issue number6
DOIs
StatePublished - 1 Dec 2019

Bibliographical note

Publisher Copyright:
© 2017, Springer-Verlag Berlin Heidelberg.

Funding

Noga Alon: Research supported in part by a BSF Grant, an ISF Grant, a GIF Grant and the Israeli I-Core program. Mark Braverman: Research supported in part by NSF Awards, DMS-1128155, CCF-1525342, and CCF-1149888, a Packard Fellowship in Science and Engineering, and the Simons Collaboration on Algorithms and Geometry. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. Klim Efremenko: Research supported in part by: European Communitys Seventh Framework Programme (FP7/2007-2013) under Grant agreement number 257575. Bernhard Haeupler: Research supported in part by NSF Grants CCF-1527110 and CCF-1618280.

FundersFunder number
Israeli I-Core
National Science FoundationNSF-BSF, 1933331, CCF-1149888, CCF-1525342, DMS-1128155
Simons Foundation
Center for Selective C-H Functionalization, National Science Foundation
Seventh Framework ProgrammeCCF-1618280, 257575, CCF-1527110
United States-Israel Binational Science Foundation
Israel Science Foundation
Seventh Framework Programme

    Keywords

    • Coding theory
    • Computation with noise
    • Interactive coding
    • Random noise

    Fingerprint

    Dive into the research topics of 'Reliable communication over highly connected noisy networks'. Together they form a unique fingerprint.

    Cite this