Distributed averaging on digital noisy networks
(2011) Information Theory and Applications Workshop (ITA), 2011- Abstract
- We consider a class of distributed algorithms for computing arithmetic averages (average consensus) over net- works of agents connected through digital noisy broadcast channels. Our algorithms combine error-correcting codes with the classical linear consensus iterative algorithm, and do not require the agents to have knowledge of the global network structure. We improve the performance by introducing in the state-upadate a compensation for the quantization error, avoiding its accumulation. We prove almost sure convergence to state agreement, and we discuss the speed of convergence and the distance between the asymptotic value and the average of the initial values.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3124772
- author
- Carli, Ruggero ; Como, Giacomo LU ; Frasca, Paolo and Garin, Federica
- organization
- publishing date
- 2011
- type
- Contribution to conference
- publication status
- published
- subject
- conference name
- Information Theory and Applications Workshop (ITA), 2011
- conference location
- San Diego, CA, United Kingdom
- conference dates
- 2011-02-06 - 2011-02-11
- external identifiers
-
- scopus:79955774287
- language
- English
- LU publication?
- yes
- id
- 71a2fafe-851f-47e3-97be-b50d0082c0eb (old id 3124772)
- date added to LUP
- 2016-04-04 13:40:48
- date last changed
- 2022-01-30 00:45:49
@misc{71a2fafe-851f-47e3-97be-b50d0082c0eb,
abstract = {{We consider a class of distributed algorithms for computing arithmetic averages (average consensus) over net- works of agents connected through digital noisy broadcast channels. Our algorithms combine error-correcting codes with the classical linear consensus iterative algorithm, and do not require the agents to have knowledge of the global network structure. We improve the performance by introducing in the state-upadate a compensation for the quantization error, avoiding its accumulation. We prove almost sure convergence to state agreement, and we discuss the speed of convergence and the distance between the asymptotic value and the average of the initial values.}},
author = {{Carli, Ruggero and Como, Giacomo and Frasca, Paolo and Garin, Federica}},
language = {{eng}},
title = {{Distributed averaging on digital noisy networks}},
year = {{2011}},
}