Scheduling of Sensor Transmissions Based on Value of Information for Summary Statistics

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5 Citations (Scopus)

Abstract

The optimization of Value of Information (VoI) in sensor networks integrates awareness of the measured process in the communication system. However, most existing scheduling algorithms do not consider the specific needs of monitoring applications, but define VoI as a generic Mean Square Error (MSE) of the whole system state regardless of the relevance of individual components. In this letter, we consider different summary statistics, i.e., different functions of the state, which can represent the useful information for a monitoring process, particularly in safety and industrial applications. We propose policies that minimize the estimation error for different summary statistics, showing significant gains by simulation.
Original languageEnglish
Article number9768131
JournalIEEE Networking Letters
Volume4
Issue number2
Pages (from-to)92-96
Number of pages5
ISSN2576-3156
DOIs
Publication statusPublished - 1 Jun 2022

Keywords

  • Kalman filters
  • Optimal scheduling
  • Monte Carlo methods
  • Job shop scheduling
  • Covariance matrices
  • Schedules
  • Monitoring

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