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Modeling radio networks

Author(s)
Newport, Calvin Charles; Lynch, Nancy Ann
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Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/
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Abstract
We describe a modeling framework and collection of foundational composition results for the study of probabilistic distributed algorithms in synchronous radio networks. Though the radio setting has been studied extensively by the distributed algorithms community, their results rely on informal descriptions of the channel behavior and therefore lack easy comparability and are prone to error caused by definition subtleties. Our framework rectifies these issues by providing: (1) a method to precisely describe a radio channel as a probabilistic automaton; (2) a mathematical notion of implementing one channel using another channel, allowing for direct comparisons of channel strengths and a natural decomposition of problems into implementing a more powerful channel and solving the problem on the powerful channel; (3) a mathematical definition of a problem and solving a problem; (4) a pair of composition results that simplify the tasks of proving properties about channel implementation algorithms and combining problems with channel implementations. Our goal is to produce a model streamlined for the needs of the radio network algorithms community.
Date issued
2011-07-06
URI
https://hdl.handle.net/1721.1/121485
Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Journal
Distributed Computing
Publisher
Springer Science and Business Media LLC
Citation
Newport, Calvin, and Nancy Lynch. “Modeling Radio Networks.” Distributed Computing 24, no. 2, (October 2011): 101–18.
Version: Author's final manuscript
ISSN
0178-2770
1432-0452

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