Optimized Live 4K Video Multicast

4K videos are becoming increasingly popular. However, despite advances in wireless technology, streaming 4K videos over mmWave to multiple users is facing significant challenges arising from directional communication, unpredictable channel fluctuation and high bandwidth requirements. This paper develops a novel 4K layered video multicast system. We (i) develop a video quality model for layered video coding, (ii) optimize resource allocation, scheduling, and beamforming based on the channel conditions of different users, and (iii) put forward a streaming strategy that uses fountain code to avoid redundancy across multicast groups and a Leaky-Bucket-based congestion control. We realize an end-to-end system on commodity-off-the-shelf (COTS) WiGig devices. We demonstrate the effectiveness of our system with extensive testbed experiments and emulation

Contribución al desarrollo de técnicas avanzadas para la evaluación de prestaciones en la Internet de las Cosas

[SPA] Las nuevas tendencias tecnológicas apuntan hacia la agregación de tecnologías simplificando su uso y control, una mayor integración con el usuario, así como un aumento exponencial del número de dispositivos conectados. Todo se engloba bajo el concepto Internet of Things (IoT) entorno un gran abanico de aplicaciones como Industria 4.0 o Smart-City, donde el vínculo con el usuario es más estrecho. La tendencia actual pretende dotar estos dispositivos de capacidades cognitivas permitiendo el aprendizaje y la actuación entre el mundo físico y social con la mínima interacción del ser humano. Tradicionalmente se ha venido utilizando Quality of Service (QoS) como métrica de evaluación objetiva. El presente estudio muestra un modelo holístico que mejora el rendimiento en IoT a partir de métricas basadas en el dominio “coste-beneficio”. El dominio beneficio está compuesto por Quality of Data (QoD), Quality of Information (QoI) y Quality of user Experience (QoE). Y el dominio coste, queda constituido únicamente por Quality Cost (QC). Estas métricas efectúan evaluaciones objetivas y subjetivas en diferentes capas de la red siendo esenciales en dispositivos con recursos limitados para la optimización de estos. En este contexto, las tecnologías Low-Power Wide Area Network (LPWAN) como Long-Range (LoRa) y Long-Range Wide Area Network (LoRaWAN) permiten comunicaciones a grandes distancias con mínimo consumo de recursos. A su vez, es una tecnología muy versátil ya que permite ser embebidos en dispositivos estáticos o móviles como Unmanned Aerial Vehicles (UAVs). Para este estudio, el uso de técnicas de Artificial Intelligent (AI) es fundamental para predecir futuros fallos en las métricas y actuar de forma previa maximizando la disponibilidad de la red.[ENG] The new technology trends aim at technology aggregation, simplifying their use and control, greater integration with the user, and an exponential increase in the number of connected devices. Everything is encompassed under the Internet of Things (IoT) concept on a wide range of applications, such as Industry 4.0 or Smart-Cities, where the relationship with the user is closer. The current trend seeks to provide these devices with cognitive capabilities to learn and act between the physical and social world with minimal human interaction. Traditionally, Quality of Service (QoS) has been used as an objective evaluation metric. The present doctoral thesis proposes a holistic model capable of offering a measurement of the services provided in IoT from metrics based on the cost-benefit domains. The benefit domain is composed by three components, which are Quality of Data (QoD), Quality of Information (QoI), and Quality of user Experience (QoE). The cost domain is made up solely of the Quality Cost (QC) component. These quality components can measure, through the use of different metrics, the performance of a service in different layers of the architecture, being essential for optimization in devices with limited resources. In this context, Low-Power Wide Area Network (LPWAN) technologies such as Long-Range (LoRa) and Long-Range Wide Area Network (LoRaWAN) allow communications over long distances with minimum resource consumption. At the same time, it is a versatile technology since it can be embedded in static or mobile devices such as Unmanned Aerial Vehicles (UAVs). For this reason, LoRa/LoRaWAN and UAVs will be used as case studies. Finally, Artificial Intelligence (AI) techniques have become an extremely useful tool in different environments, including that of performance evaluation, and above all, for its predictive capacity. For this reason, they will also be a subject of study in this doctoral thesis.Escuela Internacional de Doctorado de la Universidad Politécnica de CartagenaUniversidad Politécnica de CartagenaPrograma de Doctorado en Tecnologías de la Información y las Comunicacione

QoE management of multimedia streaming services in future networks : a tutorial and survey

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