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Pré-Publication, Document De Travail Année : 2022

Using binary tree structure for efficient monitoring strategies in a dynamic set of sensors environment for Massiv IoT paradigm

Résumé

In current monitoring solutions, each application involves a customed deployment and requires significant configuration efforts to adapt to changes in the sensor field. In contrast, here we consider a massive deployment of batterypowered sensors temporarily intervening in the monitoring. In this paper, we propose a generic general-purpose monitoring solution that is not tied to the deployment of physical devices. We develop a method that allows to receive a homogeneous amount of information per unit of time, since it is a simple and very efficient way to monitor a physical quantity that varies in time. The proposed solution limits the management costs when the sensor field is changing. Considering that the sensors enter and exit following random processes, we develop analytical results linking the function parameters-the average amount of information per unit of time-and the monitoring quality metrics-diversity, management cost. Moreover, by comparing this solution to the existing literature, we show that this solution is the most suitable for the objectives that can be considered in the context of Massive IoT.
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Dates et versions

hal-03632557 , version 1 (06-04-2022)
hal-03632557 , version 2 (20-04-2022)
hal-03632557 , version 3 (31-08-2022)
hal-03632557 , version 4 (10-10-2022)

Identifiants

  • HAL Id : hal-03632557 , version 1

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Gwen Maudet, Mireille Batton-Hubert, Patrick Maille, Laurent Toutain. Using binary tree structure for efficient monitoring strategies in a dynamic set of sensors environment for Massiv IoT paradigm. 2022. ⟨hal-03632557v1⟩
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