A lower bound for distributed averaging algorithms on the line graph
Name
Tsitsiklis_A lower bound.pdf
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307.4 KB
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Adobe PDF
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Author(s)
Tsitsiklis, John N.
Olshevsky, Alexander
Date Issued
February 2011
Journal
Proceedings of the 49th IEEE Conference on Decision and Control (CDC), 2010
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Tsitsiklis, John N. and Alexander Olshevsky. "A lower bound for distributed averaging algorithms on the line graph." Proceedings of the 2010 IEEE Conference on Decision and Control (CDC): 4523-4528. © 2010 IEEE.
Version
Final published version
Abstract
We derive lower bounds on the convergence speed of a widely used class of distributed averaging algorithms. In particular, we prove that any distributed averaging algorithm whose state consists of a single real number and whose (possibly nonlinear) update function satisfies a natural smoothness condition has a worst case running time of at least on the order of n[superscript 2] on a line network of n nodes. Our results suggest that increased memory or expansion of the state space is crucial for improving the running times of distributed averaging algorithms.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/CDC.2010.5716968
