Efficient distributed sensing using adaptive censoring based inference

Beipeng Mu, Girish Chowdhary, Jonathan P. How

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In many distributed sensing applications it is likely that only a few agents will have valuable information at any given time. Since wireless communication between agents is resource-intensive, it is important to ensure that the communication effort is focused on communicating valuable information from informative agents. This paper presents communication-efficient distributed sensing algorithms that avoid network cluttering by having only agents with high Value of Information (VoI) broadcast their measurements to the network, while others censor themselves. A novel contribution of the presented distributed estimation algorithm is the use of an adaptively adjusted VoI threshold to determine which agents are informative. This adaptation enables the team to better balance between the communication cost incurred and the long-term accuracy of the estimation. Theoretical results are presented establishing the almost sure convergence of the communication cost and estimation error to zero for distributions in the exponential family. Furthermore, validation through real datasets shows that the new VoI-based algorithms can yield improved parameter estimates than those achieved by previously published hyperparameter consensus algorithms while incurring only a fraction of the communication cost.

Original languageEnglish (US)
Title of host publication2013 American Control Conference, ACC 2013
Pages4153-4158
Number of pages6
StatePublished - 2013
Externally publishedYes
Event2013 1st American Control Conference, ACC 2013 - Washington, DC, United States
Duration: Jun 17 2013Jun 19 2013

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619

Other

Other2013 1st American Control Conference, ACC 2013
Country/TerritoryUnited States
CityWashington, DC
Period6/17/136/19/13

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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