ENERGY EFFICIENCY VIA HETEROGENEOUS NETWORK

The mobile telecommunication industry is growing at a phenomenal rate. On a daily basis, there are continuous inflow of mobile users and sophisticated devices into the mobile network. This has triggered a meteoric rise in mobile traffic; forcing network operators to embark on a series of projects to increase the capacity and coverage of mobile networks in line with growing traffic demands. A corollary to this development is the momentous rise in energy bills for mobile operators and the emission of a significant amount of CO2 into the atmosphere. This has become worrisome to the extent that regulatory bodies and environmentalist are calling for the adoption of more “green operation” to curtail these challenges. Green communication is an all-inclusive approach that champions the cause of overall network improvement, reduction in energy consumption and mitigation of carbon emission. The emergence of Heterogeneous network came as a means of fulfilling the vision of Green communication. Heterogeneous network is a blend of low power node overlaid on Macrocell to offload traffic from the Macrocell and enhance quality of service of cell edge users. Heterogeneous network seeks to boost the performance of LTE-Advanced beyond its present limit, and at the same time, reduce energy consumption in mobile wireless network. In this thesis, we explore the potential of heterogeneous network in enhancing the energy efficiency of mobile wireless network. Simulation process sees the use of a co-deployment of Macrocell and Picocell in cluster (Hot spot) and normal scenario. Finally, we compared the performance of each scenario using Cell Energy Efficiency and the Area Energy Efficiency as our performance metricfi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Aerial-terrestrial communications: terrestrial cooperation and energy-efficient transmissions to aerial-base stations

Hybrid aerial-terrestrial communication networks based on low-altitude platforms are expected to meet optimally the urgent communication needs of emergency relief and recovery operations for tackling large-scale natural disasters. The energy-efficient operation of such networks is important given that the entire network infrastructure, including the battery-operated ground terminals, exhibits requirements to operate under power-constrained situations. In this paper, we discuss the design and evaluation of an adaptive cooperative scheme intended to extend the survivability of the battery-operated aerial-terrestrial communication links. We propose and evaluate a real-time adaptive cooperative transmission strategy for dynamic selection between direct and cooperative links based on the channel conditions for improved energy efficiency. We show that the cooperation between mobile terrestrial terminals on the ground could improve energy efficiency in the uplink, depending on the temporal behavior of the terrestrial and aerial uplink channels. The corresponding delay in having cooperative (relay-based) communications with relay selection is also addressed. The simulation analysis corroborates that the adaptive transmission technique improves overall energy efficiency of the network whilst maintaining low latency, enabling real-time applications

Contribution to design a communication framework for vehicular ad hoc networks in urban scenarios

The constant mobility of people, the growing need to be always connected, the large number of vehicles that nowadays can be found in the roads and the advances in technology make Vehicular Ad hoc Networks (VANETs) be a major area of research. Vehicular Ad hoc Networks are a special type of wireless Mobile Ad hoc Networks (MANETs), which allow a group of mobile nodes configure a temporary network and maintain it without the need of a fixed infrastructure. A vehicular network presents some specific characteristics, as the very high speed of nodes. Due to this high speed the topology changes are frequent and the communication links may last only a few seconds. Smart cities are now a reality and have a direct relationship with vehicular networks. With the help of existing infrastructure such as traffic lights, we propose a scheme to update and analyse traffic density and a warning system to spread alert messages. With this, traffic lights assist vehicular networks to take proper decisions. This would ensure less congested streets. It would also be possible that the routing protocol forwards data packets to vehicles on streets with enough neighbours to increase the possibility of delivering the packets to destination. Sharing updated, reliable and real-time information, about traffic conditions, weather or security alerts, increases the need of algorithms for the dissemination of information that take into account the main beneffits and constraints of these networks. For all this, routing protocols for vehicular networks have the difficult task to select and establish transmission links to send the data packets from source to destination through multiple nodes using intermediate vehicles efficiently. The main objective of this thesis is to provide improvements in the communication framework for vehicular networks to improve decisions to select next hops in the moment to send information, in this way improving the exchange of information to provide suitable communication to minimize accidents, reduce congestion, optimize resources for emergencies, etc. Also, we include intelligence to vehicles at the moment to take routing decisions. Making them map-aware, being conscious of the presence of buildings and other obstacles in urban environments. Furthermore, our proposal considers the decision to store packets for a maximum time until finding other neighbouring nodes to forward the packets before discarding them. For this, we propose a protocol that considers multiple metrics that we call MMMR (A Multimetric, Map-Aware Routing Protocol ). MMMR is a protocol based on geographical knowledge of the environment and vehicle location. The metrics considered are the distance, the density of vehicles in transmission range, the available bandwidth and the future trajectory of the neighbouring nodes. This allows us to have a complete view of the vehicular scenario to anticipate the driver about possible changes that may occur. Thus, a node can select a node among all its neighbours, which is the best option to increase the likelihood of successful packet delivery, minimizing time and offering a level of quality and service. In the same way, being aware of the increase of information in wireless environments, we analyse the possibility of offering anonymity services. We include a mechanism of anonymity in routing protocols based on the Crowd algorithm, which uses the idea of hiding the original source of a packet. This allowed us to add some level of anonymity on VANET routing protocols. The analytical modeling of the available bandwidth between nodes in a VANET, the use of city infrastructure in a smart way, the forwarding selection in data routing byvehicles and the provision of anonymity in communications, are issues that have been addressed in this PhD thesis. In our research work we provide contributions to improve the communication framework for Vehicular Ad hoc Networks obtaining benefits toenhance the everyday of the population.La movilidad constante de las personas y la creciente necesidad de estar conectados en todo momento ha hecho de las redes vehiculares un área cuyo interés ha ido en aumento. La gran cantidad de vehículos que hay en la actualidad, y los avances tecnológicos han hecho de las redes vehiculares (VANETS, Vehicular Ad hoc Networks) un gran campo de investigación. Las redes vehiculares son un tipo especial de redes móviles ad hoc inalámbricas, las cuales, al igual que las redes MANET (Mobile Ad hoc Networks), permiten a un grupo de nodos móviles tanto configurar como mantener una red temporal por si mismos sin la necesidad de una infraestructura fija. Las redes vehiculares presentan algunas características muy representativas, por ejemplo, la alta velocidad que pueden alcanzar los nodos, en este caso vehículos. Debido a esta alta velocidad la topología cambia frecuentemente y la duración de los enlaces de comunicación puede ser de unos pocos segundos. Estas redes tienen una amplia área de aplicación, pudiendo tener comunicación entre los mismos nodos (V2V) o entre los vehículos y una infraestructura fija (V2I). Uno de los principales desafíos existentes en las VANET es la seguridad vial donde el gobierno y fabricantes de automóviles han centrado principalmente sus esfuerzos. Gracias a la rápida evolución de las tecnologías de comunicación inalámbrica los investigadores han logrado introducir las redes vehiculares dentro de las comunicaciones diarias permitiendo una amplia variedad de servicios para ofrecer. Las ciudades inteligentes son ahora una realidad y tienen una relación directa con las redes vehiculares. Con la ayuda de la infraestructura existente, como semáforos, se propone un sistema de análisis de densidad de tráfico y mensajes de alerta. Con esto, los semáforos ayudan a la red vehicular en la toma de decisiones. Así se logrará disponer de calles menos congestionadas para hacer una circulación más fluida (lo cual disminuye la contaminación). Además, sería posible que el protocolo de encaminamiento de datos elija vehículos en calles con suficientes vecinos para incrementar la posibilidad de entregar los paquetes al destino (minimizando pérdidas de información). El compartir información actualizada, confiable y en tiempo real sobre el estado del tráfico, clima o alertas de seguridad, aumenta la necesidad de algoritmos de difusión de la información que consideren los principales beneficios y restricciones de estas redes. Así mismo, considerar servicios críticos que necesiten un nivel de calidad y servicio es otro desafío importante. Por todo esto, un protocolo de encaminamiento para este tipo de redes tiene la difícil tarea de seleccionar y establecer enlaces de transmisión para enviar los datos desde el origen hacia el destino vía múltiples nodos utilizando vehículos intermedios de una manera eficiente. El principal objetivo de esta tesis es ofrecer mejoras en los sistemas de comunicación vehicular que mejoren la toma de decisiones en el momento de realizar el envío de la información, con lo cual se mejora el intercambio de información para poder ofrecer comunicación oportuna que minimice accidentes, reduzca atascos, optimice los recursos destinados a emergencias, etc. Así mismo, incluimos más inteligencia a los coches en el momento de tomar decisiones de encaminamiento de paquetes. Haciéndolos conscientes de la presencia de edificios y otros obstáculos en los entornos urbanos. Así como tomar la decisión de guardar paquetes durante un tiempo máximo de modo que se encuentre otros nodos vecinos para encaminar paquetes de información antes de descartarlo. Para esto, proponemos un protocolo basado en múltiples métricas (MMMR, A Multimetric, Map-aware Routing Protocol ) que es un protocolo geográfio basado en el conocimiento del entorno y localización de los vehículos. Las métricas consideradas son la distancia, la densidad de vehículos en el área de transmisión, el ancho de banda disponible y la trayectoria futura de los nodos vecinos. Esto nos permite tener una visión completa del escenario vehicular y anticiparnos a los posibles cambios que puedan suceder. Así, un nodo podrá seleccionar aquel nodo entre todos sus vecinos posibles que sea la mejor opción para incrementar la posibilidad de entrega exitosa de paquetes, minimizando tiempos y ofreciendo un cierto nivel de calidad y servicio. De la misma manera, conscientes del incremento de información que circula por medios inalámbricos, se analizó la posibilidad de servicios de anonimato. Incluimos pues un mecanismo de anonimato en protocolos de encaminamiento basado en el algoritmo Crowd, que se basa en la idea de ocultar la fuente original de un paquete. Esto nos permitió añadir cierto nivel de anonimato que pueden ofrecer los protocolos de encaminamiento. El modelado analítico del ancho de banda disponible entre nodos de una VANET, el uso de la infraestructura de la ciudad de una manera inteligente, la adecuada toma de decisiones de encaminamiento de datos por parte de los vehículos y la disposición de anonimato en las comunicaciones, son problemas que han sido abordados en este trabajo de tesis doctoral que ofrece contribuciones a la mejora de las comunicaciones en redes vehiculares en entornos urbanos aportando beneficios en el desarrollo de la vida diaria de la población

Adaptive Q-learning-supported Resource Allocation Model in Vehicular Fogs

Urban computing has become a significant driver in supporting the delivery and sharing of services, being a strong ally to intelligent transportation. Smart vehicles present computing and communication capabilities that allow them to enable many autonomous vehicular safety and infotainment applications. Vehicular Cloud Computing (VCC) has already proven to be a technology shifting paradigm harnessing the computation resources from on board units from vehicles to form clustered computing units to solve real world computing problems. However, with the rise of vehicular application use and intermittent network conditions, VCC exhibits many drawbacks. Vehicular Fog computing appears as a new paradigm in enabling and facilitating efficient service and resource sharing in urban environments. Several vehicular resource management works have attempted to deal with the highly dynamic vehicular environment following diverse approaches, e.g. MDP, SMDP, and policy-based greedy techniques. However, the high vehicular mobility causes several challenges compromising consistency, efficiency, and quality of service. RL-enabled adaptive vehicular Fogs can deal with the mobility for properly distributing load and resources over Fogs. Thus, we propose a mobility-based cloudlet dwell time estimation method for accurately estimating vehicular resources in a Fog. Leveraging the CDT estimation model, we devise an adaptive and highly dynamic resource allocation model using mathematical formula for Fog selection, and reinforcement learning for iterative review and feedback mechanism for generating optimal resource allocation policy

A Communications-Oriented Perspective on Traffic Management Systems for Smart Cities: Challenges and Innovative Approaches

The growing size of cities and increasing population mobility have determined a rapid increase in the number of vehicles on the roads, which has resulted in many challenges for road traffic management authorities in relation to traffic congestion, accidents, and air pollution. Over the recent years, researchers from both industry and academia have been focusing their efforts on exploiting the advances in sensing, communication, and dynamic adaptive technologies to make the existing road traffic management systems (TMSs) more efficient to cope with the aforementioned issues in future smart cities. However, these efforts are still insufficient to build a reliable and secure TMS that can handle the foreseeable rise of population and vehicles in smart cities. In this survey, we present an up-to-date review of the different technologies used in the different phases involved in a TMS and discuss the potential use of smart cars and social media to enable fast and more accurate traffic congestion detection and mitigation. We also provide a thorough study of the security threats that may jeopardize the efficiency of the TMS and endanger drivers' lives. Furthermore, the most significant and recent European and worldwide projects dealing with traffic congestion issues are briefly discussed to highlight their contribution to the advancement of smart transportation. Finally, we discuss some open challenges and present our own vision to develop robust TMSs for future smart cities

Artificial Intelligence and Cognitive Computing

Artificial intelligence (AI) is a subject garnering increasing attention in both academia and the industry today. The understanding is that AI-enhanced methods and techniques create a variety of opportunities related to improving basic and advanced business functions, including production processes, logistics, financial management and others. As this collection demonstrates, AI-enhanced tools and methods tend to offer more precise results in the fields of engineering, financial accounting, tourism, air-pollution management and many more. The objective of this collection is to bring these topics together to offer the reader a useful primer on how AI-enhanced tools and applications can be of use in today’s world. In the context of the frequently fearful, skeptical and emotion-laden debates on AI and its value added, this volume promotes a positive perspective on AI and its impact on society. AI is a part of a broader ecosystem of sophisticated tools, techniques and technologies, and therefore, it is not immune to developments in that ecosystem. It is thus imperative that inter- and multidisciplinary research on AI and its ecosystem is encouraged. This collection contributes to that

Exploring Computing Continuum in IoT Systems: Sensing, Communicating and Processing at the Network Edge

As Internet of Things (IoT), originally comprising of only a few simple sensing devices, reaches 34 billion units by the end of 2020, they cannot be defined as merely monitoring sensors anymore. IoT capabilities have been improved in recent years as relatively large internal computation and storage capacity are becoming a commodity. In the early days of IoT, processing and storage were typically performed in cloud. New IoT architectures are able to perform complex tasks directly on-device, thus enabling the concept of an extended computational continuum. Real-time critical scenarios e.g. autonomous vehicles sensing, area surveying or disaster rescue and recovery require all the actors involved to be coordinated and collaborate without human interaction to a common goal, sharing data and resources, even in intermittent networks covered areas. This poses new problems in distributed systems, resource management, device orchestration,as well as data processing. This work proposes a new orchestration and communication framework, namely CContinuum, designed to manage resources in heterogeneous IoT architectures across multiple application scenarios. This work focuses on two key sustainability macroscenarios: (a) environmental sensing and awareness, and (b) electric mobility support. In the first case a mechanism to measure air quality over a long period of time for different applications at global scale (3 continents 4 countries) is introduced. The system has been developed in-house from the sensor design to the mist-computing operations performed by the nodes. In the second scenario, a technique to transmit large amounts of fine-time granularity battery data from a moving vehicle to a control center is proposed jointly with the ability of allocating tasks on demand within the computing continuum

When Internet of Things meets Metaverse: Convergence of Physical and Cyber Worlds

In recent years, the Internet of Things (IoT) is studied in the context of the Metaverse to provide users immersive cyber-virtual experiences in mixed reality environments. This survey introduces six typical IoT applications in the Metaverse, including collaborative healthcare, education, smart city, entertainment, real estate, and socialization. In the IoT-inspired Metaverse, we also comprehensively survey four pillar technologies that enable augmented reality (AR) and virtual reality (VR), namely, responsible artificial intelligence (AI), high-speed data communications, cost-effective mobile edge computing (MEC), and digital twins. According to the physical-world demands, we outline the current industrial efforts and seven key requirements for building the IoT-inspired Metaverse: immersion, variety, economy, civility, interactivity, authenticity, and independence. In addition, this survey describes the open issues in the IoT-inspired Metaverse, which need to be addressed to eventually achieve the convergence of physical and cyber worlds.info:eu-repo/semantics/publishedVersio