Using a linear gain to accelerate average consensus over unreliable networks

Francesco  Acciani; Paolo  Frasca; Geert Heijenk; Antonie Arij Stoorvogel

doi:10.1109/CDC.2017.8264183

Using a linear gain to accelerate average consensus over unreliable networks

Francesco Acciani, Paolo Frasca, Geert Heijenk, Antonie Arij Stoorvogel

Research output: Contribution to conference › Paper › peer-review

2 Citations (Scopus)

11 Downloads (Pure)

Abstract

Packet loss is a serious issue in wireless consensus networks, as even few failures might prevent a network to converge to the correct value. However, it is possible to compensate for the errors caused by packet collisions, by modifying the updating weights. Such a modification compensates for the loss of information in an unreliable network, but results in a reduced convergence speed. In this paper, we propose a faster method — based on a suitable gain in the consensus dynamics — to solve the unreliable average consensus problem. We find a sufficient condition for the gain to preserve stability of the network. Simulations are used to discuss the choice of the gain, and to compare our method with the literature.

Original language	English
Pages	3569 - 3574
Number of pages	6
DOIs	https://doi.org/10.1109/CDC.2017.8264183
Publication status	Published - 12 Dec 2017
Event	56th IEEE Annual Conference on Decision and Control, CDC 2017 - Melbourne Convention Center, Melbourne, Australia Duration: 12 Dec 2017 → 15 Dec 2017 Conference number: 56 http://cdc2017.ieeecss.org/

Conference

Conference	56th IEEE Annual Conference on Decision and Control, CDC 2017
Abbreviated title	CDC 2017
Country/Territory	Australia
City	Melbourne
Period	12/12/17 → 15/12/17
Internet address	http://cdc2017.ieeecss.org/

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10.1109/CDC.2017.8264183

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abstract = "Packet loss is a serious issue in wireless consensus networks, as even few failures might prevent a network to converge to the correct value. However, it is possible to compensate for the errors caused by packet collisions, by modifying the updating weights. Such a modification compensates for the loss of information in an unreliable network, but results in a reduced convergence speed. In this paper, we propose a faster method — based on a suitable gain in the consensus dynamics — to solve the unreliable average consensus problem. We find a sufficient condition for the gain to preserve stability of the network. Simulations are used to discuss the choice of the gain, and to compare our method with the literature.",

author = "Francesco Acciani and Paolo Frasca and Geert Heijenk and Stoorvogel, {Antonie Arij}",

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T1 - Using a linear gain to accelerate average consensus over unreliable networks

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AU - Frasca, Paolo

AU - Heijenk, Geert

AU - Stoorvogel, Antonie Arij

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PY - 2017/12/12

Y1 - 2017/12/12

N2 - Packet loss is a serious issue in wireless consensus networks, as even few failures might prevent a network to converge to the correct value. However, it is possible to compensate for the errors caused by packet collisions, by modifying the updating weights. Such a modification compensates for the loss of information in an unreliable network, but results in a reduced convergence speed. In this paper, we propose a faster method — based on a suitable gain in the consensus dynamics — to solve the unreliable average consensus problem. We find a sufficient condition for the gain to preserve stability of the network. Simulations are used to discuss the choice of the gain, and to compare our method with the literature.

AB - Packet loss is a serious issue in wireless consensus networks, as even few failures might prevent a network to converge to the correct value. However, it is possible to compensate for the errors caused by packet collisions, by modifying the updating weights. Such a modification compensates for the loss of information in an unreliable network, but results in a reduced convergence speed. In this paper, we propose a faster method — based on a suitable gain in the consensus dynamics — to solve the unreliable average consensus problem. We find a sufficient condition for the gain to preserve stability of the network. Simulations are used to discuss the choice of the gain, and to compare our method with the literature.

U2 - 10.1109/CDC.2017.8264183

DO - 10.1109/CDC.2017.8264183

M3 - Paper

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EP - 3574

T2 - 56th IEEE Annual Conference on Decision and Control, CDC 2017

Y2 - 12 December 2017 through 15 December 2017

ER -

Using a linear gain to accelerate average consensus over unreliable networks

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