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

TL;DR

This paper proposes sensor transmission scheduling policies that optimize the Value of Information based on specific summary statistics, improving monitoring accuracy in safety and industrial applications.

Contribution

It introduces novel policies that focus on minimizing estimation error for targeted summary statistics, addressing limitations of existing VoI-based scheduling methods.

Findings

Significant reduction in estimation error demonstrated through simulations

Policies tailored to specific summary statistics outperform generic approaches

Enhanced monitoring effectiveness for safety and industrial applications

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 work, 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.