Veuillez utiliser cette adresse pour citer ce document : http://dspace1.univ-tlemcen.dz/handle/112/18641
Titre: Détection et communication coopérative pour le déploiement des réseaux de capteurs.
Auteur(s): BENAISSA, Bedr-Eddine
Mots-clés: Sensor Deployment, Data aggregation, Network Lifetime, Received signal Strength Indicator (RSSI), IoT Routing Protocol
Déploiement des capteurs, agrégation de données, durée de vie d’un réseau, Indicateur de force du signal reçu (RSSI), protocole de routage IoT
Date de publication: 5-mar-2022
Editeur: 22-06-2022
Référence bibliographique: salle des thèses
Collection/Numéro: bfst2785;
Résumé: Operating a sensor network raises many issues at several algorithmic levels: localization, deployment, data collection, coverage, and reduction of battery power consumption to optimize network lifetime. This last point has been of particular interest to the researchers. In such a network, and especially with a single-hop deployment policy, sensor measurements contain a lot of redundancy, either in the measurement dimensions of a single sensor, or between the measurement dimensions of different sensors due to spatial correlation or in the temporal dimension of measurements. The goal is to study detection and cooperation to determine conditions that will help to better position sensors in a given deployment area, while guaranteeing certain constraints related to this type of network, such as the cost of deployment and the network's lifetime. Two approaches have been proposed. The first one proposes to minimize the complexity in terms of communication and computation by relying on an aggregation and consensus system to reduce the spatial and temporal dimension of the captured data and consequently the number of deployed sensors. The results show a visible performance compared to the standard transmission method on the open platform of the COOJA / Contiki simulator allowing to simulate wireless sensor network connections and to interact with them. The second contribution minimizes the transmission frequencies of the measured data to the base station by categorizing the captured data into predefined, prenumbered classes, which we will call "confidence intervals". In this way, each captured value will be classified into a class and only its number will be sent to the base station, if (and only if) a class change with respect to the previous value is observed. The results show that interval-based data collection significantly reduces the energy of the motes' sensors. Thus, in a wireless sensor network, optimal deployment is accentuated by good data transmission management to the sink.
URI/URL: http://dspace.univ-tlemcen.dz/handle/112/18641
Collection(s) :Doctorat LMD RSD

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