Anwendung von maschinellem Lernen in der optischen Nachrichtenübertragungstechnik

Aufgrund des zunehmenden Datenverkehrs wird erwartet, dass die optischen Netze zukünftig mit höheren Systemkapazitäten betrieben werden. Dazu wird bspw. die kohärente Übertragung eingesetzt, bei der das Modulationsformat erhöht werden kann, erforder jedoch ein größeres SNR. Um dies zu erreichen, wird die optische Signalleistung erhöht, wodurch die Datenübertragung durch die nichtlinearen Beeinträchtigungen gestört wird. Der Schwerpunkt dieser Arbeit liegt auf der Entwicklung von Modellen des maschinellen Lernens, die auf diese nichtlineare Signalverschlechterung reagieren. Es wird die Support-Vector-Machine (SVM) implementiert und als klassifizierende Entscheidungsmaschine verwendet. Die Ergebnisse zeigen, dass die SVM eine verbesserte Kompensation sowohl der nichtlinearen Fasereffekte als auch der Verzerrungen der optischen Systemkomponenten ermöglicht. Das Prinzip von EONs bietet eine Technologie zur effizienten Nutzung der verfügbaren Ressourcen, die von der optischen Faser bereitgestellt werden. Ein Schlüsselelement der Technologie ist der bandbreitenvariable Transponder, der bspw. die Anpassung des Modulationsformats oder des Codierungsschemas an die aktuellen Verbindungsbedingungen ermöglicht. Um eine optimale Ressourcenauslastung zu gewährleisten wird der Einsatz von Algorithmen des Reinforcement Learnings untersucht. Die Ergebnisse zeigen, dass der RL-Algorithmus in der Lage ist, sich an unbekannte Link-Bedingungen anzupassen, während vergleichbare heuristische Ansätze wie der genetische Algorithmus für jedes Szenario neu trainiert werden müssen

Evaluation of unidirectional background push content download services for the delivery of television programs

Este trabajo de tesis presenta los servicios de descarga de contenido en modo push como un mecanismo eficiente para el envío de contenido de televisión pre-producido sobre redes de difusión. Hoy en día, los operadores de red dedican una cantidad considerable de recursos de red a la entrega en vivo de contenido televisivo, tanto sobre redes de difusión como sobre conexiones unidireccionales. Esta oferta de servicios responde únicamente a requisitos comerciales: disponer de los contenidos televisivos en cualquier momento y lugar. Sin embargo, desde un punto de vista estrictamente académico, el envío en vivo es únicamente un requerimiento para el contenido en vivo, no para contenidos que ya han sido producidos con anterioridad a su emisión. Más aún, la difusión es solo eficiente cuando el contenido es suficientemente popular. Los servicios bajo estudio en esta tesis utilizan capacidad residual en redes de difusión para enviar contenido pre-producido para que se almacene en los equipos de usuario. La propuesta se justifica únicamente por su eficiencia. Por un lado, genera valor de recursos de red que no se aprovecharían de otra manera. Por otro lado, realiza la entrega de contenidos pre-producidos y populares de la manera más eficiente: sobre servicios de descarga de contenidos en difusión. Los resultados incluyen modelos para la popularidad y la duración de contenidos, valiosos para cualquier trabajo de investigación basados en la entrega de contenidos televisivos. Además, la tesis evalúa la capacidad residual disponible en redes de difusión, por medio de estudios empíricos. Después, estos resultados son utilizados en simulaciones que evalúan las prestaciones de los servicios propuestos en escenarios diferentes y para aplicaciones diferentes. La evaluación demuestra que este tipo de servicios son un recurso muy útil para la entrega de contenido televisivo.This thesis dissertation presents background push Content Download Services as an efficient mechanism to deliver pre-produced television content through existing broadcast networks. Nowadays, network operators dedicate a considerable amount of network resources to live streaming live, through both broadcast and unicast connections. This service offering responds solely to commercial requirements: Content must be available anytime and anywhere. However, from a strictly academic point of view, live streaming is only a requirement for live content and not for pre-produced content. Moreover, broadcasting is only efficient when the content is sufficiently popular. The services under study in this thesis use residual capacity in broadcast networks to push popular, pre-produced content to storage capacity in customer premises equipment. The proposal responds only to efficiency requirements. On one hand, it creates value from network resources otherwise unused. On the other hand, it delivers popular pre-produced content in the most efficient way: through broadcast download services. The results include models for the popularity and the duration of television content, valuable for any research work dealing with file-based delivery of television content. Later, the thesis evaluates the residual capacity available in broadcast networks through empirical studies. These results are used in simulations to evaluate the performance of background push content download services in different scenarios and for different applications. The evaluation proves that this kind of services can become a great asset for the delivery of television contentFraile Gil, F. (2013). Evaluation of unidirectional background push content download services for the delivery of television programs [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/31656TESI

Sistema de Video-on-Demand para IPTV

Tese de mestrado integrado. Engenharia Electrotécnica e de Computadores. Universidade do Porto. Faculdade de Engenharia. 201

Augmenting CCAM Infrastructure for Creating Smart Roads and Enabling Autonomous Driving

Autonomous vehicles and smart roads are not new concepts and the undergoing development to empower the vehicles for higher levels of automation has achieved initial milestones. However, the transportation industry and relevant research communities still require making considerable efforts to create smart and intelligent roads for autonomous driving. To achieve the results of such efforts, the CCAM infrastructure is a game changer and plays a key role in achieving higher levels of autonomous driving. In this paper, we present a smart infrastructure and autonomous driving capabilities enhanced by CCAM infrastructure. Meaning thereby, we lay down the technical requirements of the CCAM infrastructure: identify the right set of the sensory infrastructure, their interfacing, integration platform, and necessary communication interfaces to be interconnected with upstream and downstream solution components. Then, we parameterize the road and network infrastructures (and automated vehicles) to be advanced and evaluated during the research work, under the very distinct scenarios and conditions. For validation, we demonstrate the machine learning algorithms in mobility applications such as traffic flow and mobile communication demands. Consequently, we train multiple linear regression models and achieve accuracy of over 94% for predicting aforementioned demands on a daily basis. This research therefore equips the readers with relevant technical information required for enhancing CCAM infrastructure. It also encourages and guides the relevant research communities to implement the CCAM infrastructure towards creating smart and intelligent roads for autonomous driving

Analysis of Single Board Architectures Integrating Sensors Technologies

Development boards, Single-Board Computers (SBCs) and Single-Board Microcontrollers (SBMs) integrating sensors and communication technologies have become a very popular and interesting solution in the last decade. They are of interest for their simplicity, versatility, adaptability, ease of use and prototyping, which allow them to serve as a starting point for projects and as reference for all kinds of designs. In this sense, there are innumerable applications integrating sensors and communication technologies where they are increasingly used, including robotics, domotics, testing and measurement, Do-It-Yourself (DIY) projects, Internet of Things (IoT) devices in the home or workplace and science, technology, engineering, educational and also academic world for STEAM (Science, Technology, Engineering and Mathematics) skills. The interest in single-board architectures and their applications have caused that all electronics manufacturers currently develop low-cost single board platform solutions. In this paper we realized an analysis of the most important topics related with single-board architectures integrating sensors. We analyze the most popular platforms based on characteristics as: cost, processing capacity, integrated processing technology and opensource license, as well as power consumption (mA@V), reliability (%), programming flexibility, support availability and electronics utilities. For evaluation, an experimental framework has been designed and implemented with six sensors (temperature, humidity, CO2/TVOC, pressure, ambient light and CO) and different data storage and monitoring options: locally on a µSD (Micro Secure Digital), on a Cloud Server, on a Web Server or on a Mobile ApplicationThis research was partially supported by the Centro Científico Tecnológico de Huelva (CCTH), University of Huelv

Mission Information and Test Systems Summary of Accomplishments, 2011

This annual report covers the activities of the NASA DRFC Mission Information and Test Systems, which includes the Western Aeronautical Test Range, the Simulation Engineering Branch, the Information Services and the Dryden Technical Laboratory (Flight Loads Lab). This report contains highlights, current projects and various awards achieved during in 201