With industry expectations of billions of Internet-connected things, commonly referred to as the IoT, we see a growing demand for high-performance on-chip bus architectures with the following attributes: small scale, low energy, high security, and highly configurable structures for integration, verification, and performance estimation. Our research thus mainly focuses on addressing these key problems and finding the balance among all these requirements that often work against each other. First of all, we proposed a low-cost and low-power System-on-Chips (SoCs) architecture (IBUS) that can frame data transfers differently. The IBUS protocol provides two novel transfer modes – the block and state modes, and is also backward compatible with the conventional linear mode. In order to evaluate the bus performance automatically and accurately, we also proposed an evaluation methodology based on the standard circuit design flow. Experimental results show that the IBUS based design uses the least hardware resource and reduces energy consumption to a half of an AMBA Advanced High-Performance Bus (AHB) and Advanced eXensible Interface (AXI). Additionally, the valid bandwidth of the IBUS based design is 2.3 and 1.6 times, respectively, compared with the AHB and AXI based implementations. As IoT advances, privacy and security issues become top tier concerns in addition to the high performance requirement of embedded chips. To leverage limited resources for tiny size chips and overhead cost for complex security mechanisms, we further proposed an advanced IBUS architecture to provide a structural support for the block-based AES algorithm. Our results show that the IBUS based AES-encrypted design costs less in terms of hardware resource and dynamic energy (60.2%), and achieves higher throughput (x1.6) compared with AXI. Effectively dealing with the automation in design and verification for mixed-signal integrated circuits is a critical problem, particularly when the bus architecture is new. Therefore, we further proposed a configurable and synthesizable IBUS design methodology. The flexible structure, together with bus wrappers, direct memory access (DMA), AES engine, memory controller, several mixed-signal verification intellectual properties (VIPs), and bus performance models (BPMs), forms the basic for integrated circuit design, allowing engineers to integrate application-specific modules and other peripherals to create complex SoCs.

Recent improvements in the area of Internet of Things (IoT) has led to extensive utilization of embedded devices and sensors. Hence, along with utilization the need for safety and security of these devices also increases proportionately. In the last two decades, the side-channel attack (SCA) has become a massive threat to the interrelated embedded devices. Moreover, extensive research has led to the development of many different forms of SCA for extracting the secret key by utilizing the various leakage information. Lately, machine learning (ML) based models have been more effective in breaking complex encryption systems than the other types of SCA models. However, these ML or DL models require a lot of data for training that cannot be collected while attacking a device in a real-world situation. Thus, in this thesis, we try to solve this issue by proposing the new technique of leakage conversion. In this technique, we try to convert the high signal to noise ratio (SNR) power traces to low SNR averaged electromagnetic traces. In addition to that, we also show how artificial neural networks (ANN) can learn various non-linear dependencies of features in leakage information, which cannot be done by adaptive digital signal processing (DSP) algorithms. Initially, we successfully convert traces in the time interval of 80 to 200 as the cryptographic operations occur in that time frame. Next, we show the successful conversion of traces lying in any time frame as well as having a random key and plain text values. Finally, to validate our leakage conversion technique and the generated traces we successfully implement correlation electromagnetic analysis (CEMA) with an approximate minimum traces to disclosure (MTD) of 480.

Récemment, l'intégration entre les environnements informatiques et de réseautage a été largement promu pour fournir des services intelligents à des utilisateurs finaux ainsi que l'utilisation efficace des ressources. Cette convergence a ouvert la voie à l'émergence de l'internet des objets (IdO). Le paradigme de l'IdO repose principalement sur la fabrication d'objets, appelés les choses, disparaître et se tissent dans le tissu de notre vie de tous les jours pour nous soutenir dans l'accomplissement des activités quotidiennes. L'évolutivité et l'hétérogénéité sont parmi les principaux défis qui entravent la réalisation à grande échelle de services de l'IdO dans la vie quotidienne des utilisateurs. Afin de relever les défis de l'IdO, un nouveau volet de recherche est venu en avant dans la littérature comme une classe paradigmatique des Cyber-physiques systèmes sociaux (CSPR), qui est connu comme l'Internet social des choses (Siot). Le SIOT se fonde sur la notion soulignée par phénomène petite-monde où la structure sociale permettant relation sociale fondée sur la confiance entre les personnes et les objets, d'une manière qui ressemble à des services de réseaux sociaux traditionnels (SNS) est suggérée de relever les défis de l'IdO. Cependant, depuis SIOT hérite des caractéristiques de différents informatiques et de réseautage environnements (par exemple, l'IdO et SNS) cela, en fait, augmente la quantité et la variété des données contextuelles qui doit être manipulé pour Adaptive fourniture de services dans Siot, qui agit comme le principal défi adressé dans cette thèse. Autrement dit, dans cette thèse, nous proposons la notion de contexte cognitif lorsque, dans certaine situation spatio-temporelle, le raisonnement sur les aspects objectifs du cadre, ce qui représente l'environnement physique, avec le contexte subjective, qui représente les aspects comportementaux et sociaux, est considéré comme l'amélioration des services SIOT intelligence et la capacité d'adaptation aux besoins conjoncturels des utilisateurs. Nous envisageons technologies du Web sémantique pour déployer notre contexte cognitif proposé dans deux domaines d'application; sensible au contexte recommandation des tâches quotidiennes dans les maisons intelligentes et structure sociale dépendant de la situation des choses. Un prototype de preuve de concept a été développé pour chaque domaine d'application, dans le but de démontrer l'intégration harmonieuse des objets sur le Web pour la réalisation de certaines applications. Nos résultats empiriques montrent un niveau de service amélioré l'adaptabilité et la complexité en temps de fonctionner lors de l'application de notre contexte cognitif suggéré / The paradigm of the Social Internet of Things (SIoT) is being promoted in the literature to boost a new trend wherein the benefits of social network services are exhibited within the network of connected objects i.e., the Internet of Things (IoT). The novel user-friendly interaction framework of the SIoT opens the doors for enhancing the intelligence required to stimulate a shift in the IoT from a heterogeneous network of independently connected objects towards a manageable network of everything. In practice, achieving scalability within the large-scale and the heterogeneous paradigm of the IoT while maintaining on top of its user-friendly and intuitive services to bridge human-to-machine perceptions and encourage the technology’s adaptation is a major challenge which is hindering the realization and deployment of the IoT technologies and applications into people’s daily live. For the goal of handling IoT challenges, as well as improve the level of smart services adaptability to users’ situational needs, in this thesis, novel SIoT-based application architecture is provided. That is, Semantic Web Technologies are envisaged as a means to develop automated, value-added services for SIoT. While, interoperability and automation are essential requirement to seamlessly integrate such services into user life, Ontologies are used to semantically describe Web services with the aim of enabling the automatic invocation and composition of these services as well as support interactions across the cyber, physical and social worlds. On the other hand, handling the variety of contextual data in SIoT for intelligent decision making is another big challenge which is still in very early stages of research. In this thesis we propose a cognitive reasoning approach taking into consideration achieving situational-awareness (SA) in SIoT. This reasoning approach is deployed within two application domains where results show an improved level of services adaptability compared to location-aware services which are previously proposed in the literature

As technology is growing at a fast pace, IoT-based smart home services are increasingly adopted by people. IoT-based smart homes offer numerous unimaginable benefits, including efficiency, safety, effectiveness, scalability of services, devices, and data, among many others. However, there is another side to this technology: security threats. As IoT-based technology is distributed in nature, implementing security measures and policies to protect the infrastructure becomes very difficult. The infrastructure faces threats such as information theft, eavesdropping, distortion, and more. Ensuring the security of smart home IoT devices is a critical concern, and user behavior plays a major role in achieving it. Furthermore, Theory of Planned Behavior (TPB) was utilized throughout the study. This study employed a qualitative research methodology and content analysis technique to investigate the impact of user behavior on the security of smart home IoT devices. The findings revealed several themes, such as the significance of comprehending and resolving security issues, the implementation of security measures, and the impact of user education and awareness. The study offered fresh perspectives on IoT device security and will aid in developing security best practices / I takt med att tekniken växer i snabb takt, anammas IoT-baserade smarta hemtjänster alltmer av människor. IoT-baserade smarta hem erbjuder många ofattbara fördelar, inklusive effektivitet, säkerhet, effektivitet, skalbarhet för tjänster, enheter och data, bland många andra. Däremot är en annan sida av denna teknik: säkerhetshot. Som IoT-baserad teknik distribueras i natur, att implementera säkerhetsåtgärder och policyer för att skydda infrastrukturen blir mycketsvår. Infrastrukturen står inför hot som informationsstöld, avlyssning, förvrängning och Mer. Att säkerställa säkerheten för smarta hem IoT-enheter är en kritisk fråga, och användarnas beteende spelar en stor roll för att uppnå det. Dessutom användes Theory of Planned Behavior (TPB).under hela studien. Denna studie använde en kvalitativ forskningsmetodik och innehållanalysteknik för att undersöka hur användarbeteendet påverkar säkerheten för IoT för smarta hemenheter. Fynden avslöjade flera teman, såsom betydelsen av att förstå och lösa säkerhetsfrågor, implementering av säkerhetsåtgärder och användarens inverkanutbildning och medvetenhet. Studien erbjöd nya perspektiv på IoT-enhetssäkerhet och kommer att hjälpa att utveckla bästa praxis för säkerhet / نظرًا لأن التكنولوجيا تنمو بوتيرة سريعة ، يتم اعتماد خدمات المنزل الذكي القائمة على إنترنت الأشياء بشكل متزايد من قبل الناس. توفر المنازل الذكية القائمة على إنترنت الأشياء العديد من المزايا التي لا يمكن تصورها ، بما في ذلك الكفاءة والأمان والفعالية وقابلية التوسع في الخدمات والأجهزة والبيانات ، من بين أشياء أخرى كثيرة. ومع ذلك ، هناك جانب آخر لهذه التكنولوجيا: التهديدات الأمنية. نظرًا لتوزيع التكنولوجيا القائمة على إنترنت الأشياء بطبيعتها ، يصبح تنفيذ التدابير والسياسات الأمنية لحماية البنية التحتية أمرًا صعبًا للغاية. تواجه البنية التحتية تهديدات مثل سرقة المعلومات والتنصت والتشويه والمزيد. يعد ضمان أمان أجهزة إنترنت الأشياء المنزلية الذكية مصدر قلق بالغ ، ويلعب سلوك المستخدم دورًا رئيسيًا في تحقيق ذلك. علاوة على ذلك ، تم استخدام نظرية السلوك المخطط (TPB) طوال الدراسة. استخدمت هذه الدراسة منهجية البحث النوعي وتقنية تحليل المحتوى للتحقيق في تأثير سلوك المستخدم على أمن أجهزة إنترنت الأشياء المنزلية الذكية. كشفت النتائج عن عدة محاور ، مثل أهمية فهم وحل المشكلات الأمنية ، وتنفيذ التدابير الأمنية ، وتأثير تثقيف المستخدمين وتوعيتهم. قدمت الدراسة وجهات نظر جديدة حول أمن أجهزة إنترنت الأشياء وستساعد في تطوير أفضل الممارسات الأمنية

The use of Internet of Things systems has increased to meet the need for smart systems in various fields, such as smart homes, intelligent industries, medical systems, agriculture, and the military. IoT networks are expanding daily to include hundreds and thousands of IoT devices, which transmit information through other linked devices to reach the network sink or gateway. The information follows different routes to the network sink. Finding an ideal routing solution is a big challenge due to several factors, such as power, computation, storage, and memory limitation for IoT devices. In 2011, A new standardized routing protocol for low-power and lossy networks was released by the Internet Engineering task force (IETF). The IETF adopted a distance vector routing algorithm for the RPL protocol. RPL protocol utilizes the objective functions (OFs) to select the path depending on diffident metrics.These OFs with different metrics must be evaluated and tested to develop the best routing solution.This project aims to test the performance of standardized RPL objective functions in a simulation environment. Afterwards, a new objective function with a new metric will be implemented and tested in the same environmental conditions. The performance results of the standard objective functions and the newly implemented objective function will be analyzed and compared to evaluate whether the standard objective functions or the new objective function is better as a routing solution for the IoT devices network.

The oil and gas industry faces a lack of compact drilling devices capable of performing horizontal drilling maneuvers in depleted or abandoned wells in order to enhance oil recovery. The purpose of this project was to design and develop a smart sensing system that can be later implemented in compact drilling devices used to perform horizontal drilling to enhance oil recovery in wells. A smart sensor is the combination of a sensing element (sensor) and a microprocessor. Hence, a smart sensing system is an arrangement that consists of different sensors, where one or more have smart capabilities. The sensing system was built and tested in a laboratory setting. For this, a test bench was used as a case study to simulate the operation from a micro-drilling device. The smart sensing system integrated the sensors essential for the direct operational measurements required for the robot. The focus was on selecting reliable and sturdy components that can handle the operation Down the Hole (DTH) on the final lateral micro-drilling robot. The sensing system's recorded data was sent to a microcontroller, where it was processed and then presented visually to the operator through a User Interface (UI) developed in a cloud-based framework. The information was filtered, processed, and sent to a controller that executed commands and sent signals to the test bench’s actuators. The smart sensing system included novel modules and sensors suitable for the operation in a harsh environment such as the one faced in the drilling process. Furthermore, it was designed as an independent, flexible module that can be implemented in test benches with different settings and early robotic prototypes. The outcome of this project was a sensing system able to provide robotic drilling devices with flexibility while providing accurate and reliable measurements during their operation.

In the rapidly evolving landscape of the Internet of Things (IoT), ensuring consistency and reliability becomes a top priority for a seamless user experience. In many instances, reliability is assessed through Quality of Service (QoS) metrics, sidelining traditional reliability metrics that thrive on time-dependent failure rates. The lack of a comprehensive framework that fully integrates all layers of an IoT system adds to the complexity. This gap makes it difficult to pinpoint specific areas that need improvement and to conduct a thorough assessment of the system’s reliability. This project addresses this intricate challenge, which holds significant relevance for industry professionals but remains unresolved. The project introduced an IoT architecture spanning the Power, Device, Edge, Application, and Cloud Layers. Within each layer, potential failure points were identified, and the reliability was analysed deploying time-based failure rates with an exponential distribution. Reliability Block Diagrams (RBDs) were employed to map the intricate inter-dependencies, though the framework’s adaptive nature allows for other system reliability methodologies. One of the primary outcomes of this research is the development of a new framework tailored for evaluating the reliability of various IoT system components. This framework yields insights into both system reliability and availability over time, serving as a pivotal tool for stakeholders such as device manufacturers, system integrators, network providers, and research institutions. The results show how the framework emerges as a pivotal starting point for IoT system reliability evaluation. Before this thesis, the feasibility of such a framework was uncertain, with concerns about its potential bias – being either too pessimistic or optimistic. Yet, the tangible results from this work affirm its capability to provide a balanced and reasonable reliability estimation, given the intricacies of IoT devices. This paves the way for subsequent research, enabling a deeper dive into targeted enhancements and fostering a nuanced understanding of IoT reliability. / I det snabbt föränderliga IoT-landskapet (Internet of Things) är det av högsta prioritet att säkerställa konsekvens och tillförlitlighet för en sömlös användarupplevelse. I många fall bedöms tillförlitligheten med hjälp av QoSmått (Quality of Service), vilket innebär att traditionella tillförlitlighetsmått som bygger på tidsberoende felfrekvenser åsidosätts. Avsaknaden av ett heltäckande ramverk som integrerar alla lager i ett IoT-system bidrar till komplexiteten. Denna brist gör det svårt att identifiera specifika områden som behöver förbättras och att göra en grundlig bedömning av systemets tillförlitlighet. Detta projekt tar itu med denna komplicerade utmaning, som har stor relevans för branschfolk men som fortfarande inte har lösts. Projektet introducerade en IoT-arkitektur som spänner över kraft-, enhets-, Edge-, applikationsoch molnlagren. Inom varje lager identifierades potentiella felpunkter och tillförlitligheten analyserades med hjälp av tidsbaserade felfrekvenser med en exponentiell fördelning. Tillförlitlighetsblockdiagram (RBD) användes för att kartlägga de komplicerade ömsesidiga beroendena, även om ramverkets adaptiva natur möjliggör andra metoder för systemtillförlitlighet. Ett av de främsta resultaten av denna forskning är utvecklingen av ett nytt ramverk som är skräddarsytt för att utvärdera tillförlitligheten hos olika IoT-systemkomponenter. Detta ramverk ger insikter om både systemets tillförlitlighet och tillgänglighet över tid, och fungerar som ett viktigt verktyg för intressenter som tillverkare av enheter, systemintegratörer, nätverksleverantörer och forskningsinstitutioner. Resultaten visar hur ramverket framstår som en viktig utgångspunkt för utvärdering av IoT-systemens tillförlitlighet. Före den här avhandlingen var det osäkert om ett sådant ramverk var genomförbart, med farhågor om dess potentiella partiskhet - att vara antingen för pessimistisk eller optimistisk. De konkreta resultaten från detta arbete bekräftar dock ramverkets förmåga att ge en balanserad och rimlig uppskattning av tillförlitligheten, med tanke på IoT-enheternas komplexitet. Detta banar väg för efterföljande forskning, vilket möjliggör en djupare analys av riktade förbättringar och främjar en nyanserad förståelse av IoT-tillförlitlighet.

<p dir="ltr">This project aimed to develop an instrumentation and control system for a micro-drilling robot based on Industrial Internet of Things (IIoT) technologies. The automation system integrated IIoT technological tools to create a robust automation system capable of being used in drilling operations. The system incorporated industrial-grade sensors, which carried out direct measurements of the critical variables of the process. The indirect variables relevant to the control of the robot were calculated from the measured parameters. The system also considered the telemetry architecture necessary to reliably transmit data from the down-the-hole (DTH) robot to a receiver on the surface. Telemetry was based on wireless communication through long-range radio frequency (LoRa). The system developed had models based on Artificial Intelligence (AI) and Machine Learning (ML) for determining the mode of operation, detecting changes in the process, and changes in drilling variables in critical hydraulic components for the drilling process. Algorithms based on AI and ML models also allowed the user to make better decisions based on the variables' correlation to optimize the drilling process (e.g., dynamic change of flow, pressure, and RPMs based on automatic rock identification). A user interface (UI) was developed, and digital tools to perform data analysis were implemented. Safety assessment in all robot systems (e.g., electrical, hardware, software) was contemplated as a critical design component. The result of this research project provides innovative micro-drilling robots with the necessary technological tools to optimize the drilling process. The system made drilling more efficient, reliable, and safe, providing diagnostic and prognostic tools that allowed planning maintenance based on the actual health of the devices. The system that was developed was tested in a test bench under controlled conditions within a laboratory to characterize the system and collect data that allowed ML models' development, training, validation, and testing. The prototype of a micro-drilling robot installed on the test bench served as a case study to assess the implemented models' reliability and the proposed telemetry.</p>

La quinta generación de redes móviles (5G) se encuentra a la vuelta de la esquina. Se espera provea de beneficios extraordinarios a la población y que resuelva la mayoría de los problemas de las redes 4G actuales. El éxito de 5G, cuya primera fase de estandarización ha sido completada, depende de tres pilares: comunicaciones tipo-máquina masivas, banda ancha móvil mejorada y comunicaciones ultra fiables y de baja latencia (mMTC, eMBB y URLLC, respectivamente). En esta tesis nos enfocamos en el primer pilar de 5G, mMTC, pero también proveemos una solución para lograr eMBB en escenarios de distribución masiva de contenidos. Específicamente, las principales contribuciones son en las áreas de: 1) soporte eficiente de mMTC en redes celulares; 2) acceso aleatorio para el reporte de eventos en redes inalámbricas de sensores (WSNs); y 3) cooperación para la distribución masiva de contenidos en redes celulares. En el apartado de mMTC en redes celulares, esta tesis provee un análisis profundo del desempeño del procedimiento de acceso aleatorio, que es la forma mediante la cual los dispositivos móviles acceden a la red. Estos análisis fueron inicialmente llevados a cabo por simulaciones y, posteriormente, por medio de un modelo analítico. Ambos modelos fueron desarrollados específicamente para este propósito e incluyen uno de los esquemas de control de acceso más prometedores: access class barring (ACB). Nuestro modelo es uno de los más precisos que se pueden encontrar en la literatura y el único que incorpora el esquema de ACB. Los resultados obtenidos por medio de este modelo y por simulación son claros: los accesos altamente sincronizados que ocurren en aplicaciones de mMTC pueden causar congestión severa en el canal de acceso. Por otro lado, también son claros en que esta congestión se puede prevenir con una adecuada configuración del ACB. Sin embargo, los parámetros de configuración del ACB deben ser continuamente adaptados a la intensidad de accesos para poder obtener un desempeño óptimo. En la tesis se propone una solución práctica a este problema en la forma de un esquema de configuración automática para el ACB; lo llamamos ACBC. Los resultados muestran que nuestro esquema puede lograr un desempeño muy cercano al óptimo sin importar la intensidad de los accesos. Asimismo, puede ser directamente implementado en redes celulares para soportar el tráfico mMTC, ya que ha sido diseñado teniendo en cuenta los estándares del 3GPP. Además de los análisis descritos anteriormente para redes celulares, se realiza un análisis general para aplicaciones de contadores inteligentes. Es decir, estudiamos un escenario de mMTC desde la perspectiva de las WSNs. Específicamente, desarrollamos un modelo híbrido para el análisis de desempeño y la optimización de protocolos de WSNs de acceso aleatorio y basados en cluster. Los resultados muestran la utilidad de escuchar el medio inalámbrico para minimizar el número de transmisiones y también de modificar las probabilidades de transmisión después de una colisión. En lo que respecta a eMBB, nos enfocamos en un escenario de distribución masiva de contenidos, en el que un mismo contenido es enviado de forma simultánea a un gran número de usuarios móviles. Este escenario es problemático, ya que las estaciones base de la red celular no cuentan con mecanismos eficientes de multicast o broadcast. Por lo tanto, la solución que se adopta comúnmente es la de replicar e contenido para cada uno de los usuarios que lo soliciten; está claro que esto es altamente ineficiente. Para resolver este problema, proponemos el uso de esquemas de network coding y de arquitecturas cooperativas llamadas nubes móviles. En concreto, desarrollamos un protocolo para la distribución masiva de contenidos, junto con un modelo analítico para su optimización. Los resultados demuestran que el modelo propuesto es simple y preciso, y que el protocolo puede reducir el con / La cinquena generació de xarxes mòbils (5G) es troba molt a la vora. S'espera que proveïsca de beneficis extraordinaris a la població i que resolga la majoria dels problemes de les xarxes 4G actuals. L'èxit de 5G, per a la qual ja ha sigut completada la primera fase del qual d'estandardització, depén de tres pilars: comunicacions tipus-màquina massives, banda ampla mòbil millorada, i comunicacions ultra fiables i de baixa latència (mMTC, eMBB i URLLC, respectivament, per les seues sigles en anglés). En aquesta tesi ens enfoquem en el primer pilar de 5G, mMTC, però també proveïm una solució per a aconseguir eMBB en escenaris de distribució massiva de continguts. Específicament, les principals contribucions són en les àrees de: 1) suport eficient de mMTC en xarxes cel·lulars; 2) accés aleatori per al report d'esdeveniments en xarxes sense fils de sensors (WSNs); i 3) cooperació per a la distribució massiva de continguts en xarxes cel·lulars. En l'apartat de mMTC en xarxes cel·lulars, aquesta tesi realitza una anàlisi profunda de l'acompliment del procediment d'accés aleatori, que és la forma mitjançant la qual els dispositius mòbils accedeixen a la xarxa. Aquestes anàlisis van ser inicialment dutes per mitjà de simulacions i, posteriorment, per mitjà d'un model analític. Els models van ser desenvolupats específicament per a aquest propòsit i inclouen un dels esquemes de control d'accés més prometedors: el access class barring (ACB). El nostre model és un dels més precisos que es poden trobar i l'únic que incorpora l'esquema d'ACB. Els resultats obtinguts per mitjà d'aquest model i per simulació són clars: els accessos altament sincronitzats que ocorren en aplicacions de mMTC poden causar congestió severa en el canal d'accés. D'altra banda, també són clars en què aquesta congestió es pot previndre amb una adequada configuració de l'ACB. No obstant això, els paràmetres de configuració de l'ACB han de ser contínuament adaptats a la intensitat d'accessos per a poder obtindre unes prestacions òptimes. En la tesi es proposa una solució pràctica a aquest problema en la forma d'un esquema de configuració automàtica per a l'ACB; l'anomenem ACBC. Els resultats mostren que el nostre esquema pot aconseguir un acompliment molt proper a l'òptim sense importar la intensitat dels accessos. Així mateix, pot ser directament implementat en xarxes cel·lulars per a suportar el trànsit mMTC, ja que ha sigut dissenyat tenint en compte els estàndards del 3GPP. A més de les anàlisis descrites anteriorment per a xarxes cel·lulars, es realitza una anàlisi general per a aplicacions de comptadors intel·ligents. És a dir, estudiem un escenari de mMTC des de la perspectiva de les WSNs. Específicament, desenvolupem un model híbrid per a l'anàlisi de prestacions i l'optimització de protocols de WSNs d'accés aleatori i basats en clúster. Els resultats mostren la utilitat d'escoltar el mitjà sense fil per a minimitzar el nombre de transmissions i també de modificar les probabilitats de transmissió després d'una col·lisió. Pel que fa a eMBB, ens enfoquem en un escenari de distribució massiva de continguts, en el qual un mateix contingut és enviat de forma simultània a un gran nombre d'usuaris mòbils. Aquest escenari és problemàtic, ja que les estacions base de la xarxa cel·lular no compten amb mecanismes eficients de multicast o broadcast. Per tant, la solució que s'adopta comunament és la de replicar el contingut per a cadascun dels usuaris que ho sol·liciten; és clar que això és altament ineficient. Per a resoldre aquest problema, proposem l'ús d'esquemes de network coding i d'arquitectures cooperatives anomenades núvols mòbils. En concret, desenvolupem un protocol per a realitzar la distribució massiva de continguts de forma eficient, juntament amb un model analític per a la seua optimització. Els resultats demostren que el model proposat és simple i precís / The 5th generation (5G) of mobile networks is just around the corner. It is expected to bring extraordinary benefits to the population and to solve the majority of the problems of current 4th generation (4G) systems. The success of 5G, whose first phase of standardization has concluded, relies in three pillars that correspond to its main use cases: massive machine-type communication (mMTC), enhanced mobile broadband (eMBB), and ultra-reliable low latency communication (URLLC). This thesis mainly focuses on the first pillar of 5G: mMTC, but also provides a solution for the eMBB in massive content delivery scenarios. Specifically, its main contributions are in the areas of: 1) efficient support of mMTC in cellular networks; 2) random access (RA) event-reporting in wireless sensor networks (WSNs); and 3) cooperative massive content delivery in cellular networks. Regarding mMTC in cellular networks, this thesis provides a thorough performance analysis of the RA procedure (RAP), used by the mobile devices to switch from idle to connected mode. These analyses were first conducted by simulation and then by an analytical model; both of these were developed with this specific purpose and include one of the most promising access control schemes: the access class barring (ACB). To the best of our knowledge, this is one of the most accurate analytical models reported in the literature and the only one that incorporates the ACB scheme. Our results clearly show that the highly-synchronized accesses that occur in mMTC applications can lead to severe congestion. On the other hand, it is also clear that congestion can be prevented with an adequate configuration of the ACB scheme. However, the configuration parameters of the ACB scheme must be continuously adapted to the intensity of access attempts if an optimal performance is to be obtained. We developed a practical solution to this problem in the form of a scheme to automatically configure the ACB; we call it access class barring configuration (ACBC) scheme. The results show that our ACBC scheme leads to a near-optimal performance regardless of the intensity of access attempts. Furthermore, it can be directly implemented in 3rd Generation Partnership Project (3GPP) cellular systems to efficiently handle mMTC because it has been designed to comply with the 3GPP standards. In addition to the analyses described above for cellular networks, a general analysis for smart metering applications is performed. That is, we study an mMTC scenario from the perspective of event detection and reporting WSNs. Specifically, we provide a hybrid model for the performance analysis and optimization of cluster-based RA WSN protocols. Results showcase the utility of overhearing to minimize the number of packet transmissions, but also of the adaptation of transmission parameters after a collision occurs. Building on this, we are able to provide some guidelines that can drastically increase the performance of a wide range of RA protocols and systems in event reporting applications. Regarding eMBB, we focus on a massive content delivery scenario in which the exact same content is transmitted to a large number of mobile users simultaneously. Such a scenario may arise, for example, with video streaming services that offer a particularly popular content. This is a problematic scenario because cellular base stations have no efficient multicast or broadcast mechanisms. Hence, the traditional solution is to replicate the content for each requesting user, which is highly inefficient. To solve this problem, we propose the use of network coding (NC) schemes in combination with cooperative architectures named mobile clouds (MCs). Specifically, we develop a protocol for efficient massive content delivery, along with the analytical model for its optimization. Results show the proposed model is simple and accurate, and the protocol can lead to energy savings of up to 37 percent when compared to the traditional approach. / Leyva Mayorga, I. (2018). On reliable and energy efficient massive wireless communications: the road to 5G [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/115484