Optimization of MAC mechanisms for energy management in Wireless Sensor Networks / Lakhdar Goudjil  

Public ISBD Titre : Optimization of MAC mechanisms for energy management in Wireless Sensor Networks Type de document : document électronique Auteurs : Lakhdar Goudjil, Auteur ; Fouzi Semchedine, Directeur de thèse Année de publication : 2023 Importance : 1 vol (103 f .) Format : 29cm Langues : Français (fre) Catégories : Thèses & Mémoires:Informatique Mots-clés : Receiver:initiated Cooperation Energy saving Optimization of MAC wireless sensor networks Index. décimale : 004 Informatique Résumé : Power consumption is the most important factor to evaluate the performance of Wireless Sensor Networks (WSNs). Most sensor network Medium Access Control (MAC) protocols operate based on a duty cycle mechanism. The asynchronous receiver-initiated MAC duty cycle protocols are popular due to their relatively higher energy efficiency. However, recent advances harnessing the benefits of cooperative communication have become one of the solutions of MAC duty cycle protocol. In this thesis, we improve the RI-MAC protocol by introducing a short frame identifier to notify the sender when the receiver wakes up. This resolution reduces idle listening, which increases energy performance. When the sender node receives a short frame identifier, it cooperates with neighboring senders, which minimizes collisions. Our protocol is called: a Cooperative Short Frame Identifier Receiver Initiated MAC protocol, COSFI-RIMAC is an asynchronous MAC protocol cooperative service cycle initiated by the receiver. The simulation result on the NS2 simulator shows that the COSFI-RIMAC mechanism reduces power consumption, produces minor latency, and increases the rate of packet delivery. Côte titre : DI/0074 En ligne : http://dspace.univ-setif.dz:8888/jspui/handle/123456789/4085 Format de la ressource électronique : PDF Optimization of MAC mechanisms for energy management in Wireless Sensor Networks [document électronique] / Lakhdar Goudjil, Auteur ; Fouzi Semchedine, Directeur de thèse . - 2023 . - 1 vol (103 f .) ; 29cm. Langues : Français (fre) Catégories : Thèses & Mémoires:Informatique Mots-clés : Receiver:initiated Cooperation Energy saving Optimization of MAC wireless sensor networks Index. décimale : 004 Informatique Résumé : Power consumption is the most important factor to evaluate the performance of Wireless Sensor Networks (WSNs). Most sensor network Medium Access Control (MAC) protocols operate based on a duty cycle mechanism. The asynchronous receiver-initiated MAC duty cycle protocols are popular due to their relatively higher energy efficiency. However, recent advances harnessing the benefits of cooperative communication have become one of the solutions of MAC duty cycle protocol. In this thesis, we improve the RI-MAC protocol by introducing a short frame identifier to notify the sender when the receiver wakes up. This resolution reduces idle listening, which increases energy performance. When the sender node receives a short frame identifier, it cooperates with neighboring senders, which minimizes collisions. Our protocol is called: a Cooperative Short Frame Identifier Receiver Initiated MAC protocol, COSFI-RIMAC is an asynchronous MAC protocol cooperative service cycle initiated by the receiver. The simulation result on the NS2 simulator shows that the COSFI-RIMAC mechanism reduces power consumption, produces minor latency, and increases the rate of packet delivery. Côte titre : DI/0074 En ligne : http://dspace.univ-setif.dz:8888/jspui/handle/123456789/4085 Format de la ressource électronique : PDF

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
DI/0074	DI/0074	Thèse	Bibliothéque des sciences	Anglais	Disponible Disponible

Smart bracelet for Epilepsy Monitoring / Lamia Belaaz

Public ISBD Titre : Smart bracelet for Epilepsy Monitoring Type de document : document électronique Auteurs : Lamia Belaaz ; Fouzi Semchedine, Directeur de thèse Editeur : Setif:UFA Année de publication : 2024 Importance : 1 vol (57 f .) Format : 29 cm Langues : Anglais (eng) Catégories : Thèses & Mémoires:Informatique Mots-clés : Informatique Index. décimale : 004 Informatique Résumé : Epilepsy is a chronic neurological condition characterized by unpredictable and often dangerous seizures, posing significant challenges for patients and healthcare providers. Traditional methods for seizure detection rely on stationary systems or patient-reported observations, which can result in delayed interventions and inaccurate monitoring. To address this, our research focuses on developing a smart wearable device for real-time epilepsy monitoring. Utilizing sensors such as ECG, pulse, and the MPU-6050 accelerometer and gyroscope, the device captures physiological data, which is processed using machine learning models deployed on an ESP32 microcontroller. This innovative system aims to detect tonic-clonic seizures accurately and alert caregivers promptly, improving patient safety and quality of life. The motivation behind this project is to contribute to a suite of advanced research solutions that empower neurologists and healthcare professionals to better understand and manage epilepsy. This wearable device not only facilitates continuous monitoring but also opens avenues for enhanced data-driven diagnosis and treatment. Future developments aim to incorporate additional sensors, such as EEG, and refine algorithms for more precise detection, making this technology a vital tool in modern epilepsy care Note de contenu : Sommaire Côte titre : MAI/0961 Smart bracelet for Epilepsy Monitoring [document électronique] / Lamia Belaaz ; Fouzi Semchedine, Directeur de thèse . - [S.l.] : Setif:UFA, 2024 . - 1 vol (57 f .) ; 29 cm. Langues : Anglais (eng) Catégories : Thèses & Mémoires:Informatique Mots-clés : Informatique Index. décimale : 004 Informatique Résumé : Epilepsy is a chronic neurological condition characterized by unpredictable and often dangerous seizures, posing significant challenges for patients and healthcare providers. Traditional methods for seizure detection rely on stationary systems or patient-reported observations, which can result in delayed interventions and inaccurate monitoring. To address this, our research focuses on developing a smart wearable device for real-time epilepsy monitoring. Utilizing sensors such as ECG, pulse, and the MPU-6050 accelerometer and gyroscope, the device captures physiological data, which is processed using machine learning models deployed on an ESP32 microcontroller. This innovative system aims to detect tonic-clonic seizures accurately and alert caregivers promptly, improving patient safety and quality of life. The motivation behind this project is to contribute to a suite of advanced research solutions that empower neurologists and healthcare professionals to better understand and manage epilepsy. This wearable device not only facilitates continuous monitoring but also opens avenues for enhanced data-driven diagnosis and treatment. Future developments aim to incorporate additional sensors, such as EEG, and refine algorithms for more precise detection, making this technology a vital tool in modern epilepsy care Note de contenu : Sommaire Côte titre : MAI/0961

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
MAI/0961	MAI/0961	Mémoire	Bibliothéque des sciences	Anglais	Disponible Disponible

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