Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Convergence of Limited Communications Gradient Methods
KTH, School of Electrical Engineering (EES), Network and Systems engineering. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-6617-8683
KTH, School of Electrical Engineering (EES), Network and Systems engineering. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0001-9810-3478
Show others and affiliations
(English)Article in journal (Other academic) Submitted
Abstract [en]

Distributed optimization increasingly plays a centralrole in economical and sustainable operation of cyber-physicalsystems. Nevertheless, the complete potential of the technologyhas not yet been fully exploited in practice due to communicationlimitations posed by the real-world infrastructures. This workinvestigates fundamental properties of distributed optimizationbased on gradient methods, where gradient information iscommunicated using limited number of bits. In particular, ageneral class of quantized gradient methods are studied wherethe gradient direction is approximated by a finite quantizationset. Sufficient and necessary conditions are provided on sucha quantization set to guarantee that the methods minimize anyconvex objective function with Lipschitz continuous gradient anda nonempty and bounded set of optimizers. A lower bound on thecardinality of the quantization set is provided, along with specificexamples of minimal quantizations. Convergence rate results areestablished that connect the fineness of the quantization andthe number of iterations needed to reach a predefined solutionaccuracy. Generalizations of the results to a relevant class ofconstrained problems using projections are considered. Finally,the results are illustrated by simulations of practical systems.

National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-205666OAI: oai:DiVA.org:kth-205666DiVA, id: diva2:1090040
Note

QC 20170424

Available from: 2017-04-21 Created: 2017-04-21 Last updated: 2017-04-24Bibliographically approved
In thesis
1. Bandwidth Limited Distributed Optimization with Applications to Networked Cyberphysical Systems
Open this publication in new window or tab >>Bandwidth Limited Distributed Optimization with Applications to Networked Cyberphysical Systems
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The emerging technology of Cyberphysical systems consists of networked computing, sensing, and actuator devices used to monitor, connect, and control physical phenomena. In order to economically and sustainably operate Cyberphysical systems, their devices need to cooperate over a communication network to solve optimization problems. For example, in smart power grids, smart meters cooperatively optimize the grid performance, and in wireless sensor networks a number of sensors cooperate to find optimal estimators of real-world parameters. A challenging aspect in the design of distributed solution algorithms to these optimization problems is that while the technology advances and the networks grow larger, the communication bandwidth available to coordinate the solution remains limited. Motivated by this challenge, this thesis investigates the convergence of distributed solution methods for resource allocation optimization problems, where gradient information is communicated at every iteration, using limited communication. This problem is approached from three different perspectives, each presented in a separate paper.  The investigation of the three papers demonstrate promises and limits of solving distributed resource allocation problems using limited communication bandwidth. Future work will consider how even more general problems can be solved using limited communication bandwidth and also study different communication constraints.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2017. p. 142
Series
TRITA-EE, ISSN 1653-5146 ; 2017:031
Keywords
Distributed Optimization, Resource Allocation, Power Networks, Limited Communication, Networks, Cyberphysical Systems, Wireless Sensor Networks, Internet of Things
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-205682 (URN)978-91-7729-356-9 (ISBN)
Public defence
2017-05-12, D3, Lindstedtsvägen 9, Stockholm, 10:00 (English)
Opponent
Supervisors
Note

QC 20170424

Available from: 2017-04-24 Created: 2017-04-21 Last updated: 2017-04-25Bibliographically approved

Open Access in DiVA

No full text in DiVA

Authority records BETA

Magnússon, SindriFischione, Carlo

Search in DiVA

By author/editor
Magnússon, SindriFischione, Carlo
By organisation
Network and Systems engineeringACCESS Linnaeus Centre
Electrical Engineering, Electronic Engineering, Information Engineering

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 21 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf