Desarrollo de un sistema de transmisión de contenidos entre drones y vehículos mediante difusión

In recent years, the use of drones has rapidly spread due to their wide scope of application. On the other hand, vehicular networks have evolved very fast because the vehicles are equipped with wireless communication devices. If we integrate these two elements, drones and vehicular networks, very interesting and highly novel solutions can be achieved. In this work, we develop a system for the delivery of the contents from a drone equipped with Raspberry Pi to terrestrial vehicles (cars, buses, trucks, etc). The information (image, voice, image+voice or short video) will be encoded at the application level using Raptor codes (Forward Error Correction), and then broadcasted using IEEE 802.11a technology, being simultaneously received by any number of the vehicles, and then rebuilt and displayed in an Android terminal. The proposed Content Delivery System has reached its final development status, and has successfully been tested experimentally. Test have been performed using different mobile devices, allowing us to perform a comparative study to determine which devices are better adapted to our system.En los últimos años el uso de drones se está extendiendo rápidamente debido a los muchos campos de aplicación que tienen. Por otro lado, las redes vehiculares están evolucionando muy rápido debido a que los vehículos están equipados con dispositivos de comunicación inalámbrica. Si integramos estos dos elementos, drones y redes vehiculares, se pueden realizar trabajos muy interesantes y altamente novedosos. El objetivo de este proyecto es el desarrollo de un sistema para entrega de contenidos desde un dron equipado con Raspberry Pi hacia vehículos terrestres (coches, autobuses, camiones, etc.). La información (imagen, voz, imagen+voz o video corto) será codificada a nivel de aplicación usando códigos Raptor (Forward Error Correction), y después difundida usando tecnología IEEE 802.11a, siendo alcanzada simultáneamente por un número cualquiera de vehículos receptores, y a continuación reconstruida y visualizada en un terminal Android. El sistema de entrega de contenido se ha completado en su totalidad y ha sido probado experimentalmente con éxito. Las pruebas han sido realizadas utilizando diferentes dispositivos móviles, lo cual nos ha permitido realizar un estudio comparativo para ver qué dispositivos se adaptan mejor a nuestro sistema.Ortiz Mayordomo, S. (2017). Desarrollo de un sistema de transmisión de contenidos entre drones y vehículos mediante difusión. http://hdl.handle.net/10251/86057TFG

Scalable Video Streaming with Prioritised Network Coding on End-System Overlays

PhDDistribution over the internet is destined to become a standard approach for live broadcasting of TV or events of nation-wide interest. The demand for high-quality live video with personal requirements is destined to grow exponentially over the next few years. Endsystem multicast is a desirable option for relieving the content server from bandwidth bottlenecks and computational load by allowing decentralised allocation of resources to the users and distributed service management. Network coding provides innovative solutions for a multitude of issues related to multi-user content distribution, such as the coupon-collection problem, allocation and scheduling procedure. This thesis tackles the problem of streaming scalable video on end-system multicast overlays with prioritised push-based streaming. We analyse the characteristic arising from a random coding process as a linear channel operator, and present a novel error detection and correction system for error-resilient decoding, providing one of the first practical frameworks for Joint Source-Channel-Network coding. Our system outperforms both network error correction and traditional FEC coding when performed separately. We then present a content distribution system based on endsystem multicast. Our data exchange protocol makes use of network coding as a way to collaboratively deliver data to several peers. Prioritised streaming is performed by means of hierarchical network coding and a dynamic chunk selection for optimised rate allocation based on goodput statistics at application layer. We prove, by simulated experiments, the efficient allocation of resources for adaptive video delivery. Finally we describe the implementation of our coding system. We highlighting the use rateless coding properties, discuss the application in collaborative and distributed coding systems, and provide an optimised implementation of the decoding algorithm with advanced CPU instructions. We analyse computational load and packet loss protection via lab tests and simulations, complementing the overall analysis of the video streaming system in all its components

Network streaming and compression for mixed reality tele-immersion

Bulterman, D.C.A. [Promotor]Cesar, P.S. [Copromotor

Forward error correction with RaptorQ code on GPU

RaptorQ code, the next generation of Raptor code for forward error correction (FEC), is proposed to significantly reduce the redundant information. However, the improved coding performance comes at the expense of increased encoding and decoding complexity. On the other hand, graphics processing units (GPUs) are finding their way beyond graphics processing into general purpose computing in the consumer market. This paper investigates the suitability of GPU for RaptorQ code to process large block and symbol sizes in FEC transmission. The paper explores serial and parallel implementations of Raptor code on CPU and GPU, respectively. Our work shows that efficient parallelization on the GPU can improve the performance of the decoder significantly. Furthermore, simulations are performed for the practical real time requirement in multimedia broadcast/multicast service (MBMS) and digital video broadcasting (DVB) in highspeed downlink packet access (HSDPA) network. Conclusions are drawn with respect to the applicability of this new code for realtime multimedia broadcasting and content delivery on GPU. © 2013 IEEE