This paper investigates remote sensing networks and discusses different models to characterize the Value of Information (VoI), a metric that describes how informative the data transmitted by the sensors are. For each sensor, the VoI evaluations comprise the average node-specific Age of Information (AoI), the average cost spent for sending updates, and the AoI of neighbor nodes, assumed to be correlated sources of information and therefore benefiting the VoI of other sensors nearby. We discuss how this metric can be tracked through a two-dimensional Markov chain, but we also show how this representation can be simplified by including the impact of neighbor nodes within the transition probabilities, so as to obtain a simpler model that gives the same insight in terms of VoI evaluations.
Zancanaro, A., Cisotto, G., Badia, L. (2022). Modeling Value of Information in Remote Sensing from Correlated Sources. In 2022 20th Mediterranean Communication and Computer Networking Conference, MedComNet 2022 (pp.47-53) [10.1109/MedComNet55087.2022.9810457].
Modeling Value of Information in Remote Sensing from Correlated Sources
Cisotto, G
;
2022
Abstract
This paper investigates remote sensing networks and discusses different models to characterize the Value of Information (VoI), a metric that describes how informative the data transmitted by the sensors are. For each sensor, the VoI evaluations comprise the average node-specific Age of Information (AoI), the average cost spent for sending updates, and the AoI of neighbor nodes, assumed to be correlated sources of information and therefore benefiting the VoI of other sensors nearby. We discuss how this metric can be tracked through a two-dimensional Markov chain, but we also show how this representation can be simplified by including the impact of neighbor nodes within the transition probabilities, so as to obtain a simpler model that gives the same insight in terms of VoI evaluations.File | Dimensione | Formato | |
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