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Reliable communication over highly connected noisy networks

  • Noga Alon
  • , Mark Braverman
  • , Klim Efremenko
  • , Ran Gelles*
  • , Bernhard Haeupler
  • *Corresponding author for this work
  • Princeton University
  • Tel Aviv University
  • Bar-Ilan University
  • Carnegie Mellon University

Research output: Contribution to journalArticlepeer-review

17 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

Funding

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

    Keywords

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

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