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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Veröffentlicht in:	IEEE transactions on control of network systems Jg. 5; H. 1; S. 167 - 178
Hauptverfasser:	Shuai Liu, Lihua Xie, Quevedo, Daniel E.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	IEEE 01.03.2018
Schlagworte:	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 surname: Shuai Liu fullname: Shuai Liu email: lius0025@ntu.edu.sg organization: Sch. of Control Sci. & Eng., Shandong Univ., Jinan, China – sequence: 2 surname: Lihua Xie fullname: Lihua Xie email: elhxie@ntu.edu.sg organization: Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore – sequence: 3 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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Snippet	A NOVEL distributed algorithm based on multiple agents with continuous-time dynamics is proposed for a convex optimization problem where the objective function...
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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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