Data Processing in the Emerging Internet of Things

الموضوعات

علوم بحتة وطبيعية

الملخص

The emergence IoT is rapidly gaining ground in our modern society, aiming to improve the quality of life byconnecting many smart devices, technologies and applications, for the purpose of exchanging data over the Internet. IoTdevices will generate huge volumes of data in a rapid period of time and therefore require scalable solutions for dynamic andreal-time processing of the generated data. Such solutions should provide a high level of accurate and reliable data fordecision making. This requires data fusion, which is an efficient way for optimal use of a huge volume of data from multiplesources. We consider in this thesis the integration of IoT with edge, fog and cloud computing, the efficiency of dataprocessing and fusion in terms of credibility, reliability, conflict, latency, and we propose several solutions. The firstconcerns the efficient processing of data in edge computing, which enables sophisticated services. The second approach is ahybrid computing-based IoT data management and control platform that enables heterogeneous resources, reliableconnectivity and mobility, provides security, and contains services to merge data. heterogeneous. Numerical analysis andsimulation results show that the proposed solutions allow significant savings in terms of energy consumption and reductionof lead times. The thesis also considers the state estimation in the average level of data fusion. We provide an improveddistributed particulate filter algorithm to process target tracking in wireless sensor networks. It increases the estimationaccuracy of the particulate filter, improves the efficiency of particle sampling, and improves the estimation performance. Thesimulation and numerical analysis results show the superiority of the proposed approach in terms of root mean square errorand scalability. We have studied the problem of data fusion at the decision-making level. Reliability and conflicts are takeninto account in our method by considering the information lifetime, the distance between sensors and features, reducing thecomputation and using combination rules based on the base probability assignment . This makes it possible to representuncertain information or to quantify the similarity between two bodies of evidence. We compared the proposed solution withstate-of-the-art data fusion methods, and using both benchmark data simulation and an actual data set from an intelligentbuilding testbed. The results show that our solution outperforms methods in terms of reliability, accuracy and conflicthandling.

روابط وملفات

التعريف والنوع

رقم الوثيقة

02159c7b-a690-415c-9f12-bff2e966fe23

رقم العقد

0

نوع الوسائط

Crawler

نوع المحتوى

الرسائل العلمية

صيغة المصدر

رسائل دكتوراة

نوع الملف

pdf text

أسماء الملفات

918680_1.pdf

بيانات النشر

ألقاب المؤلفين

[{"name_ar":"Djamel Djenouri","title_ar":"اشراف","title_en":"Supervision"},{"name_ar":"Sahar Boulkaboul","title_ar":"اعداد","title_en":"Preparation"}]

اللغة

French

المصدر والدورية

اسم المصدر

Data Processing in the Emerging Internet of Things

المحتوى والصفحات

عدد الصفحات

0

كلمات الباحثين

Internet of Things : Edge Computing : Cloud Computing :Dempster-Shafer theory

إشراف وإعداد

الإشراف

Djamel Djenouri

الإعداد

Sahar Boulkaboul

الاقتباسات الببليوغرافية