Event-Triggered Quantized Communication-Based Distributed Convex Optimization

A NOVEL distributed algorithm based on multiple agents with continuous-time dynamics is proposed for a convex optimization problem where the objective function is the summation of local objective functions and the state of each agent is subject to a convex constraint set. Considering the limited ban...

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Published in:IEEE transactions on control of network systems Vol. 5; no. 1; pp. 167 - 178
Main Authors: Shuai Liu, Lihua Xie, Quevedo, Daniel E.
Format: Journal Article
Language:English
Published: IEEE 01.03.2018
Subjects:
Algorithm design and analysis
Broadcasting
Communication networks
Convex functions
Distributed algorithms
distributed algorithms/control
event trigger
Heuristic algorithms
Optimization
quantization
Quantization (signal)
ISSN:2325-5870, 2372-2533
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Abstract A NOVEL distributed algorithm based on multiple agents with continuous-time dynamics is proposed for a convex optimization problem where the objective function is the summation of local objective functions and the state of each agent is subject to a convex constraint set. Considering the limited bandwidth of the communication channels, we introduce a dynamic quantizer for each agent. To further save on communication costs, we develop an event-based broadcasting scheme for each agent. In comparison with algorithms that rely on continuous communication, the proposed algorithm serves to save communication expenditure by exploiting temporal and spatial aspects. Though a joint design of dynamic quantizers and event-trigger functions are under mild conditions, the states of the agents asymptotically approach the global optimal point with an adjustable error bound without incurring Zeno behavior.
AbstractList A NOVEL distributed algorithm based on multiple agents with continuous-time dynamics is proposed for a convex optimization problem where the objective function is the summation of local objective functions and the state of each agent is subject to a convex constraint set. Considering the limited bandwidth of the communication channels, we introduce a dynamic quantizer for each agent. To further save on communication costs, we develop an event-based broadcasting scheme for each agent. In comparison with algorithms that rely on continuous communication, the proposed algorithm serves to save communication expenditure by exploiting temporal and spatial aspects. Though a joint design of dynamic quantizers and event-trigger functions are under mild conditions, the states of the agents asymptotically approach the global optimal point with an adjustable error bound without incurring Zeno behavior.
Author Shuai Liu
Quevedo, Daniel E.
Lihua Xie
Author_xml – sequence: 1
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  surname: Lihua Xie
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  givenname: Daniel E.
  surname: Quevedo
  fullname: Quevedo, Daniel E.
  email: dquevedo@ieee.org
  organization: Dept. of Electr. Eng. (EIM-E), Paderborn Univ., Paderborn, Germany
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SubjectTerms Algorithm design and analysis
Broadcasting
Communication networks
Convex functions
Distributed algorithms
distributed algorithms/control
event trigger
Heuristic algorithms
Optimization
quantization
Quantization (signal)
Title Event-Triggered Quantized Communication-Based Distributed Convex Optimization
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