IEICE TRANSACTIONS on Fundamentals
Distributed Subgradient Method for Constrained Convex Optimization with Quantized and Event-Triggered Communication
Summary :
In this paper, we propose a distributed subgradient-based method over quantized and event-triggered communication networks for constrained convex optimization. In the proposed method, each agent sends the quantized state to the neighbor agents only at its trigger times through the dynamic encoding and decoding scheme. After the quantized and event-triggered information exchanges, each agent locally updates its state by a consensus-based subgradient algorithm. We show a sufficient condition for convergence under summability conditions of a diminishing step-size.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E103-A No.2 pp.428-434
- Publication Date
- 2020/02/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.2019MAP0007
- Type of Manuscript
- Special Section PAPER (Special Section on Mathematical Systems Science and its Applications)
- Category
Authors
Naoki HAYASHI
Osaka University
Kazuyuki ISHIKAWA
Osaka University
Shigemasa TAKAI
Osaka University
Keyword
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Naoki HAYASHI, Kazuyuki ISHIKAWA, Shigemasa TAKAI, "Distributed Subgradient Method for Constrained Convex Optimization with Quantized and Event-Triggered Communication" in IEICE TRANSACTIONS on Fundamentals,
vol. E103-A, no. 2, pp. 428-434, February 2020, doi: 10.1587/transfun.2019MAP0007.
Abstract: In this paper, we propose a distributed subgradient-based method over quantized and event-triggered communication networks for constrained convex optimization. In the proposed method, each agent sends the quantized state to the neighbor agents only at its trigger times through the dynamic encoding and decoding scheme. After the quantized and event-triggered information exchanges, each agent locally updates its state by a consensus-based subgradient algorithm. We show a sufficient condition for convergence under summability conditions of a diminishing step-size.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2019MAP0007/_p
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@ARTICLE{e103-a_2_428,
author={Naoki HAYASHI, Kazuyuki ISHIKAWA, Shigemasa TAKAI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Distributed Subgradient Method for Constrained Convex Optimization with Quantized and Event-Triggered Communication},
year={2020},
volume={E103-A},
number={2},
pages={428-434},
abstract={In this paper, we propose a distributed subgradient-based method over quantized and event-triggered communication networks for constrained convex optimization. In the proposed method, each agent sends the quantized state to the neighbor agents only at its trigger times through the dynamic encoding and decoding scheme. After the quantized and event-triggered information exchanges, each agent locally updates its state by a consensus-based subgradient algorithm. We show a sufficient condition for convergence under summability conditions of a diminishing step-size.},
keywords={},
doi={10.1587/transfun.2019MAP0007},
ISSN={1745-1337},
month={February},}
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TY - JOUR
TI - Distributed Subgradient Method for Constrained Convex Optimization with Quantized and Event-Triggered Communication
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 428
EP - 434
AU - Naoki HAYASHI
AU - Kazuyuki ISHIKAWA
AU - Shigemasa TAKAI
PY - 2020
DO - 10.1587/transfun.2019MAP0007
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E103-A
IS - 2
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - February 2020
AB - In this paper, we propose a distributed subgradient-based method over quantized and event-triggered communication networks for constrained convex optimization. In the proposed method, each agent sends the quantized state to the neighbor agents only at its trigger times through the dynamic encoding and decoding scheme. After the quantized and event-triggered information exchanges, each agent locally updates its state by a consensus-based subgradient algorithm. We show a sufficient condition for convergence under summability conditions of a diminishing step-size.
ER -
English
