Wake–up Control for Wireless Sensor Networks Collecting top–k Data with Temporal Correlation

Shiraishi, Junya; Yomo, Hiroyuki

doi:10.1109/vtc2020-fall49728.2020.9348549

Cited by 2 publications

(1 citation statement)

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“…The scheduling in this scenario is driven by the BS, which selects the sensor that it believes to have the most useful information at each time slot; the opposite scenario, in which sensors themselves decide whether to transmit or not, is an interesting but different problem, as it requires sensors to maintain an estimate of the system state and a decision algorithm, which consume energy, as well as to coordinate among themselves to avoid collisions. Our scenario is directly applicable to wake-up radio [11], [12] and similar schemes with low-power sensors.…”

Section: Introductionmentioning

confidence: 99%

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

Chiariotti¹,

Kalør²,

Holm³

et al. 2022

Preprint

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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.

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Section: Introductionmentioning

confidence: 99%