Nos travaux s’orientent vers les problèmes de réseaux sans fil liés à la coexistence des communications machine-to-machine (M2M) et humain-humain (H2H). On souhaite souligner l'impact mutuel entre les trafics M2M et H2H dans un contexte d’Internet des objets (IoT : Internet Of Things) en particulier lors des catastrophes. Les communications M2M, qui devraient connaître une roissance exponentielle dans un avenir proche, constitueront un facteur important pour affecter tous les réseaux mobiles. On prévoit un grand nombre d'appareils M2M qui entraînera inévitablement des problèmes de saturation et aura des impacts remarquables sur les trafics, les services et les applications M2M et H2H. Pour étudier les influences mutuelles M2M et H2H, nous développons un nouveau modèle markovien à temps continu (CTMC) pour simuler, analyser et mesurer les différentes stratégies d'accès aux réseaux sans fil. Notre modèle nous a permis de contourner certaines limitations des simulateurs professionnels de LTE-A (Long Term Evolution-Advanced) comme SimuLTE en terme d’un nombre massif d'appareils M2M, une flexibilité de certains paramètres ou pour élaborer plus des outils statistiques. Lors d’un sinistre et suite à un énorme nombre de M2M souhaitant accéder aux réseaux sans-fil, nous avons constaté un épuisement rapide de la bande passante allouée dans les réseaux LTE-M (Long Term Evolution for Machines) ou Narrow Band for IoT (NB-IoT). Pour résoudre ce problème, nous proposons une nouvelle approche appelée Adaptive eNodeB (A-eNB) pour les réseaux LTE-M et NB-IoT. Selon nos simulations, l’A-eNB peut résoudre progressivement le problème de surcharge tout en assurant une satisfaisante qualité de service (QoS) pour le trafic H2H. Avec le concept d’A-eNB, un réseau LTE-M pourra adapter ses ressources pour faire face à une augmentation progressive du nombre de connexions M2M accédant au réseau LTE-M / NB-IoT et en même temps réduire l'impact sur le trafic H2H. / This Ph.D. work aims to study the Machine-to-Machine (M2M) congestion overload problem and the mutual impact among M2M and Human-to-Human (H2H) traffics in IoT (Internet of Things) environments specifically during disaster events. M2M devices with their expected exponential booming in the near future, will be one of the significant factors to influence all mobile networks. Inevitably, the expected huge number of M2M devices causes saturation problems, and leads to remarkable impacts on both M2M and H2H traffics, services and applications. To study the M2M and H2H mutual influences, we create a new platform model based on Continuous-Time Markov Chain (CTMC) to simulate, analyze and measure radio access strategies due to the limitations of existing Long Term Evolution-Advanced (LTE-A) simulators (i.e, SimuLTE) in term of massive M2M devices, parameter flexibility and statistical tools. Additionally, during disaster events, a fast bandwidth depletion of the limited bandwidth assigned to M2M devices in Long Term Evolution for Machines (LTE-M) and Narrow Band for IoT (NB-IoT) networks is expected due to the high arrival request of M2M device network access. To address this problem, we propose a new approach named Adaptive eNodeB (A-eNB) for both LTE-M and NB-IoT networks. The A-eNB can solve gradually the overload problem, while keeping the H2H traffic Quality of Service (QoS) not to be affected badly. The network adaptation is provided through a dynamic LTE-M resource reservation aiming to increase the number of M2M connections accessing the LTE-M/NB-IoT network and to decrease the impact on H2H traffic.

This diploma thesis consists of theoretical description of M2M communication and main differences comparing with H2H communication. There is also a description of protocols used in Internet of Things and description of practical implementation of protocols WM-BUS and Z-Wave in Python programming language with usage of Django framework.

Reducing heart failure risk standardized readmissions rates (RSRRs) continues to be a challenge in the United States. Among Medicare beneficiaries, the U.S. national rate for heart failure RSRRs is 23, and Georgia only has 3 hospitals with heart failure RSRRs that are better than the national rate. The hospital component of the chronic care model (CCM) was the theoretical framework used in this study because the model was designed to assist heath care organizations in improving chronic care outcomes. Researchers have indicated that the Hospital to Home Initiative (H2H), a national quality improvement campaign launched in 2009, is effective in reducing RSSRs. However, very little research has been conducted to determine which specific H2H strategies and categories of strategies are associated with reducing heart failure RSRRs in Georgia. The purpose of this nonexperimental, cross-sectional quantitative research study was to address this gap. The H2H Survey used in this study is a valid instrument that was previously used in a national study. Surveys were sent to 35 hospitals in Georgia participating in the H2H. A series of one-way ANOVAs were used to test the hypotheses. Key findings were as follows: (a) heart failure RSRRs were reduced when hospitals implemented the H2H, (b) the number of implemented H2H strategies was associated with a reduction in heart failure RSRRs, and (c) categories of strategies were associated with a reduction in heart failure RSRRs. These findings can be used for promoting positive social change because hospital administrators can implement changes using effective strategies to reduce both heart failure RSRRs and government penalties associated with these readmissions.

The aim of this diploma thesis is to create universal application able to visualize M2M data and allows remote management of smart sensors using TR-069 protocol. First part of this thesis contains comprehensive evaluation of TR-069 standard and OSGi platform. Next, extensive analysis of embedded databases with detailed description of SQLite platform is provided. Auto-configuration server genieacs and modus TR-069 client, two parts needed for the proper run of remote configuration, are described in more detail in following section. Practical part of this thesis contains description of all created OSGi bundles together with communication interfaces. Moreover, the description of designed database and developed user interface is given.