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Erasure Correction for Noisy Radio Networks

Authors Keren Censor-Hillel , Bernhard Haeupler , D. Ellis Hershkowitz , Goran Zuzic



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Author Details

Keren Censor-Hillel
  • Technion, Haifa, Israel
Bernhard Haeupler
  • Computer Science Department, Carnegie Mellon University, Pittsburgh, PA, USA
D. Ellis Hershkowitz
  • Computer Science Department, Carnegie Mellon University, Pittsburgh, PA, USA
Goran Zuzic
  • Computer Science Department, Carnegie Mellon University, Pittsburgh, PA, USA

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Keren Censor-Hillel, Bernhard Haeupler, D. Ellis Hershkowitz, and Goran Zuzic. Erasure Correction for Noisy Radio Networks. In 33rd International Symposium on Distributed Computing (DISC 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 146, pp. 10:1-10:17, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2019)
https://doi.org/10.4230/LIPIcs.DISC.2019.10

Abstract

The radio network model is a well-studied model of wireless, multi-hop networks. However, radio networks make the strong assumption that messages are delivered deterministically. The recently introduced noisy radio network model relaxes this assumption by dropping messages independently at random. In this work we quantify the relative computational power of noisy radio networks and classic radio networks. In particular, given a non-adaptive protocol for a fixed radio network we show how to reliably simulate this protocol if noise is introduced with a multiplicative cost of poly(log Delta, log log n) rounds where n is the number nodes in the network and Delta is the max degree. Moreover, we demonstrate that, even if the simulated protocol is not non-adaptive, it can be simulated with a multiplicative O(Delta log ^2 Delta) cost in the number of rounds. Lastly, we argue that simulations with a multiplicative overhead of o(log Delta) are unlikely to exist by proving that an Omega(log Delta) multiplicative round overhead is necessary under certain natural assumptions.

Subject Classification

ACM Subject Classification
  • Theory of computation → Distributed computing models
  • Theory of computation → Distributed algorithms
  • Theory of computation → Graph algorithms analysis
Keywords
  • radio networks
  • erasure correction
  • noisy radio networks
  • protocol simulation
  • distributed computing models

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