Broadcasting in unreliable radio networks
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Lynch_Broadcasting in.pdf
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Author(s)
Kuhn, Fabian
Lynch, Nancy A.
Newport, Calvin Charles
Oshman, Rotem
Richa, Andrea
Date Issued
July 2010
Journal
Proceeding of the 29th ACM SIGACT-SIGOPS symposium on Principles of distributed computing (PODC '10)
Publisher
Association for Computing Machinery
Citation
Kuhn, Fabian et al. “Broadcasting in unreliable radio networks.” Proceeding of the 29th ACM SIGACT-SIGOPS symposium on Principles of distributed computing. Zurich, Switzerland: ACM, 2010. 336-345. © 2010 ACM
Version
Author's final manuscript
Abstract
Practitioners agree that unreliable links, which sometimes deliver messages and sometime do not, are an important characteristic of wireless networks. In contrast, most theoretical models of radio networks fix a static set of links and assume that these links are reliable. This gap between theory and practice motivates us to investigate how unreliable links affect theoretical bounds on broadcast in radio networks.
To that end we consider a model that includes two types of links: reliable links, which always deliver messages, and unreliable links, which sometimes fail to deliver messages. We assume that the reliable links induce a connected graph, and that unreliable links are controlled by a worst-case adversary. In the new model we show an Ω(n log n) lower bound on deterministic broadcast in undirected graphs, even when all processes are initially awake and have collision detection, and an Ω(n) lower bound on randomized broadcast in undirected networks of constant diameter. This separates the new model from the classical, reliable model. On the positive side, we give two algorithms that tolerate unreliability: an O(n3/2 √log n)-time deterministic algorithm and a randomized algorithm which terminates in O(n log2 n) rounds with high probability.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution-Noncommercial-Share Alike 3.0
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DOI of Published Version
https://doi.org/10.1145/1835698.1835779
