A Generic Algorithm Framework for Distributed Optimization over the Time-Varying Network with Communication Delays

Jie Liu; Daniel W. C. Ho; Lulu Li

doi:10.1109/TAC.2023.3264784

A Generic Algorithm Framework for Distributed Optimization over the Time-Varying Network with Communication Delays

Jie Liu^*
, Daniel W. C. Ho
, Lulu Li

^*Corresponding author for this work

Department of Mathematics

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

15 Citations (Scopus)

107 Downloads (CityUHK Scholars)

Abstract

In this paper, we study the distributed optimization problem (DOP) over the time-varying communication network topology with communication delays. The existing distributed optimization algorithms (DOAs) cannot be directly applied to DOPs over the time-varying network with communication delays. In this paper, by adding new virtual agents and redefining communication links, some delay properties are realized and existing DOAs can then be reused to solve the DOPs. Thus, a generic algorithm framework is established which can apply to many important DOAs, such as the mirror descent algorithm and dual averaging algorithm, to solve DOPs over the time-varying network with communication delays. The convergence results of the DOAs are established and verified under the generic algorithm framework. © 2023 IEEE.

Original language	English
Pages (from-to)	371-378
Journal	IEEE Transactions on Automatic Control
Volume	69
Issue number	1
Online published	5 Apr 2023
DOIs	https://doi.org/10.1109/TAC.2023.3264784
Publication status	Published - Jan 2024

Funding

This work was supported in part by the Research Grants Council of the Hong Kong Special Administrative Region, China, under Grant CityU 11202819 and Grant CityU 11203521 and in part by CityU Strategic Research under Grant 7005511.

Research Keywords

Communication Delays
Communication networks
Convergence
Delays
Distributed Optimization
Linear programming
Mirrors
Multiagent Network
Optimization
Time-Varying Network
Topology

Publisher's Copyright Statement

COPYRIGHT TERMS OF DEPOSITED POSTPRINT FILE: © 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Liu, J., Ho, D. W. C., & Li, L. (2023). A Generic Algorithm Framework for Distributed Optimization over the Time-Varying Network with Communication Delays. IEEE Transactions on Automatic Control, 69(1), 371 - 378. https://doi.org/10.1109/TAC.2023.3264784

RGC Funding Information

RGC-funded

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10.1109/TAC.2023.3264784

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Cite this

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title = "A Generic Algorithm Framework for Distributed Optimization over the Time-Varying Network with Communication Delays",

abstract = "In this paper, we study the distributed optimization problem (DOP) over the time-varying communication network topology with communication delays. The existing distributed optimization algorithms (DOAs) cannot be directly applied to DOPs over the time-varying network with communication delays. In this paper, by adding new virtual agents and redefining communication links, some delay properties are realized and existing DOAs can then be reused to solve the DOPs. Thus, a generic algorithm framework is established which can apply to many important DOAs, such as the mirror descent algorithm and dual averaging algorithm, to solve DOPs over the time-varying network with communication delays. The convergence results of the DOAs are established and verified under the generic algorithm framework. {\textcopyright} 2023 IEEE.",

keywords = "Communication Delays, Communication networks, Convergence, Delays, Distributed Optimization, Linear programming, Mirrors, Multiagent Network, Optimization, Time-Varying Network, Topology",

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year = "2024",

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Y1 - 2024/1

N2 - In this paper, we study the distributed optimization problem (DOP) over the time-varying communication network topology with communication delays. The existing distributed optimization algorithms (DOAs) cannot be directly applied to DOPs over the time-varying network with communication delays. In this paper, by adding new virtual agents and redefining communication links, some delay properties are realized and existing DOAs can then be reused to solve the DOPs. Thus, a generic algorithm framework is established which can apply to many important DOAs, such as the mirror descent algorithm and dual averaging algorithm, to solve DOPs over the time-varying network with communication delays. The convergence results of the DOAs are established and verified under the generic algorithm framework. © 2023 IEEE.

AB - In this paper, we study the distributed optimization problem (DOP) over the time-varying communication network topology with communication delays. The existing distributed optimization algorithms (DOAs) cannot be directly applied to DOPs over the time-varying network with communication delays. In this paper, by adding new virtual agents and redefining communication links, some delay properties are realized and existing DOAs can then be reused to solve the DOPs. Thus, a generic algorithm framework is established which can apply to many important DOAs, such as the mirror descent algorithm and dual averaging algorithm, to solve DOPs over the time-varying network with communication delays. The convergence results of the DOAs are established and verified under the generic algorithm framework. © 2023 IEEE.

KW - Communication Delays

KW - Communication networks

KW - Convergence

KW - Delays

KW - Distributed Optimization

KW - Linear programming

KW - Mirrors

KW - Multiagent Network

KW - Optimization

KW - Time-Varying Network

KW - Topology

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DO - 10.1109/TAC.2023.3264784

M3 - RGC 21 - Publication in refereed journal

SN - 0018-9286

VL - 69

SP - 371

EP - 378

JO - IEEE Transactions on Automatic Control

JF - IEEE Transactions on Automatic Control

IS - 1

ER -

A Generic Algorithm Framework for Distributed Optimization over the Time-Varying Network with Communication Delays

Abstract

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Research Keywords

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GRF: Distributed Optimization over Multi-agent Networks

GRF: Nonlinear Fusion Estimation for Networked Sensor Systems

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A Generic Algorithm Framework for Distributed Optimization over the Time-Varying Network with Communication Delays

Abstract

Funding

Research Keywords

Publisher's Copyright Statement

RGC Funding Information

Access Output

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Projects

GRF: Distributed Optimization over Multi-agent Networks

GRF: Nonlinear Fusion Estimation for Networked Sensor Systems

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