Opportunistic Routing for Multi-flow Video Dissemination over Flying Ad-Hoc Networks

A reliable and robust routing service for Flying Ad-Hoc Networks (FANETs) must be able to adapt to topology changes. User experience on watching live video sequences must also be satisfactory even in scenarios with buffer overflow and high packet loss ratio. In this paper, we introduce a Cross-layer Link quality and Geographical-aware beaconless opportunistic routing protocol (XLinGO). It enhances the transmission of simultaneous multiple video flows over FANETs by creating and keeping reliable persistent multi-hop routes. XLinGO considers a set of cross-layer and human-related information for routing decisions, as performance metrics and Quality of Experience (QoE). Performance evaluation shows that XLinGO achieves multimedia dissemination with QoE support and robustness in a multi-hop, multi-flow, and mobile network environments.

A Comparative Analysis of Beaconless Opportunistic Routing Protocols for Video Dissemination over Flying Ad-Hoc Networks

A reliable and robust routing service for Flying Ad-Hoc Networks (FANETs) must be able to adapt to topology changes, and also to recover the quality level of the delivered multiple video flows under dynamic network topologies. The user experience on watching live videos must also be satisfactory even in scenarios with network congestion, buffer overflow, and packet loss ratio, as experienced in many FANET multimedia applications. In this paper, we perform a comparative simulation study to assess the robustness, reliability, and quality level of videos transmitted via well-known beaconless opportunistic routing protocols. Simulation results shows that our developed protocol XLinGO achieves multimedia dissemination with Quality of Experience (QoE) support and robustness in a multi-hop, multi-flow, and mobile networks, as required in many multimedia FANET scenarios.

Context-aware Adaptation Mechanism for Video Dissemination over Flying Ad-Hoc Networks

The user experience on watching live video se- quences transmitted over a Flying Ad-Hoc Networks (FANETs) must be considered to drop packets in overloaded queues, in scenarios with high buffer overflow and packet loss rate. In this paper, we introduce a context-aware adaptation mechanism to manage overloaded buffers. More specifically, we propose a utility function to compute the dropping probability of each packet in overloaded queues based on video context information, such as frame importance, packet deadline, and sensing relevance. In this way, the proposed mechanism drops the packet that adds the minimum video distortion. Simulation evaluation shows that the proposed adaptation mechanism provides real-time multimedia dissemination with QoE support in a multi-hop, multi-flow, and mobile network environments.

Adaptive Beaconless Opportunistic Routing for Multimedia Distribution

User experience on watching live videos must be satisfactory even under the inuence of different network conditions and topology changes, such as happening in Flying Ad-Hoc Networks (FANETs). Routing services for video dissemination over FANETs must be able to adapt routing decisions at runtime to meet Quality of Experience (QoE) requirements. In this paper, we introduce an adaptive beaconless opportunistic routing protocol for video dissemination over FANETs with QoE support, by taking into account multiple types of context information, such as link quality, residual energy, buffer state, as well as geographic information and node mobility in a 3D space. The proposed protocol takes into account Bayesian networks to define weight vectors and Analytic Hierarchy Process (AHP) to adjust the degree of importance for the context information based on instantaneous values. It also includes a position prediction to monitor the distance between two nodes in order to detect possible route failure.

Carbohydrate Estimation by a Mobile Phone-Based System Versus Self-Estimations of Individuals With Type 1 Diabetes Mellitus: A Comparative Study

Background: Diabetes mellitus is spreading throughout the world and diabetic individuals have been shown to often assess their food intake inaccurately; therefore, it is a matter of urgency to develop automated diet assessment tools. The recent availability of mobile phones with enhanced capabilities, together with the advances in computer vision, have permitted the development of image analysis apps for the automated assessment of meals. GoCARB is a mobile phone-based system designed to support individuals with type 1 diabetes during daily carbohydrate estimation. In a typical scenario, the user places a reference card next to the dish and acquires two images using a mobile phone. A series of computer vision modules detect the plate and automatically segment and recognize the different food items, while their 3D shape is reconstructed. Finally, the carbohydrate content is calculated by combining the volume of each food item with the nutritional information provided by the USDA Nutrient Database for Standard Reference. Objective: The main objective of this study is to assess the accuracy of the GoCARB prototype when used by individuals with type 1 diabetes and to compare it to their own performance in carbohydrate counting. In addition, the user experience and usability of the system is evaluated by questionnaires. Methods: The study was conducted at the Bern University Hospital, “Inselspital” (Bern, Switzerland) and involved 19 adult volunteers with type 1 diabetes, each participating once. Each study day, a total of six meals of broad diversity were taken from the hospital’s restaurant and presented to the participants. The food items were weighed on a standard balance and the true amount of carbohydrate was calculated from the USDA nutrient database. Participants were asked to count the carbohydrate content of each meal independently and then by using GoCARB. At the end of each session, a questionnaire was completed to assess the user’s experience with GoCARB. Results: The mean absolute error was 27.89 (SD 38.20) grams of carbohydrate for the estimation of participants, whereas the corresponding value for the GoCARB system was 12.28 (SD 9.56) grams of carbohydrate, which was a significantly better performance ( P=.001). In 75.4% (86/114) of the meals, the GoCARB automatic segmentation was successful and 85.1% (291/342) of individual food items were successfully recognized. Most participants found GoCARB easy to use. Conclusions: This study indicates that the system is able to estimate, on average, the carbohydrate content of meals with higher accuracy than individuals with type 1 diabetes can. The participants thought the app was useful and easy to use. GoCARB seems to be a well-accepted supportive mHealth tool for the assessment of served-on-a-plate meals.

Trends in Human-Centric Multimedia Networking Scenarios

The evolution of wireless access technologies and mobile devices, together with the constant demand for video services, has created new Human-Centric Multimedia Networking (HCMN) scenarios. However, HCMN poses several challenges for content creators and network providers to deliver multimedia data with an acceptable quality level based on the user experience. Moreover, human experience and context, as well as network information play an important role in adapting and optimizing video dissemination. In this paper, we discuss trends to provide video dissemination with Quality of Experience (QoE) support by integrating HCMN with cloud computing approaches. We identified five trends coming from such integration, namely Participatory Sensor Networks, Mobile Cloud Computing formation, QoE assessment, QoE management, and video or network adaptation.

Modelado de sistemas de inteligencia ambiental para el entrenamiento de las cualidades físicas

En un ejercicio no extenuante la frecuencia cardíaca (FC) guarda una relación lineal con el consumo máximo de oxígeno (V O2max) y se suele usar como uno de los parámetros de referencia para cuantificar la capacidad del sistema cardiovascular. Normalmente la frecuencia cardíaca puede remplazar el porcentaje de V O2max en las prescripciones básicas de ejercicio para la mejora de la resistencia aeróbica. Para obtener los mejores resultados en la mejora de la resistencia aeróbica, el entrenamiento de los individuos se debe hacer a una frecuencia cardíaca suficientemente alta, para que el trabajo sea de predominio dinámico con la fosforilación oxidativa como fuente energética primaria, pero no tan elevada que pueda suponer un riesgo de infarto de miocardio para el sujeto que se está entrenando. Los programas de entrenamiento de base mínima y de base óptima, con ejercicios de estiramientos para prevenir lesiones, son algunos de los programas más adecuados para el entrenamiento de la resistencia aeróbica porque maximizan los beneficios y minimizan los riesgos para el sistema cardiovascular durante las sesiones de entrenamiento. En esta tesis, se ha definido un modelo funcional para sistemas de inteligencia ambiental capaz de monitorizar, evaluar y entrenar las cualidades físicas que ha sido validado cuando la cualidad física es la resistencia aeróbica. El modelo se ha implementado en una aplicación Android utilizando la camiseta inteligente “GOW running” de la empresa Weartech. El sistema se ha comparado en el Laboratorio de Fisiología del Esfuerzo (LFE) de la Universidad Politécnica de Madrid (UPM) durante la realización de pruebas de esfuerzo. Además se ha evaluado un sistema de guiado con voz para los entrenamientos de base mínima y de base óptima. También el desarrollo del software ha sido validado. Con el uso de cuestionarios sobre las experiencias de los usuarios utilizando la aplicación se ha evaluado el atractivo de la misma. Por otro lado se ha definido una nueva metodología y nuevos tipos de cuestionarios diseñados para evaluar la utilidad que los usuarios asignan al uso de un sistema de guiado por voz. Los resultados obtenidos confirman la validez del modelo. Se ha obtenido una alta concordancia entre las medidas de FC hecha por la aplicación Android y el LFE. También ha resultado que los métodos de estimación del VO2max de los dos sistemas pueden ser intercambiables. Todos los usuarios que utilizaron el sistema de guiado por voz para entrenamientos de 10 base mínima y de base óptimas de la resistencia aeróbica consiguieron llevar a cabo las sesiones de entrenamientos con un 95% de éxito considerando unos márgenes de error de un 10% de la frecuencia cardíaca máxima teórica. La aplicación fue atractiva para los usuarios y hubo también una aceptación del sistema de guiado por voz. Se ha obtenido una evaluación psicológica positiva de la satisfacción de los usuarios que interactuaron con el sistema. En conclusión, se ha demostrado que es posible desarrollar sistemas de Inteligencia Ambiental en dispositivos móviles para la mejora de la salud. El modelo definido en la tesis es el primero modelo funcional teórico de referencia para el desarrollo de este tipo de aplicaciones. Posteriores estudios se realizarán con el objetivo de extender dicho modelo para las demás cualidades físicas que suponen modelos fisiológicos más complejos como por ejemplo la flexibilidad. Abstract In a non-strenuous exercise, the heart rate (HR) shows a linear relationship with the maximum volume of oxygen consumption (V O2max) and serves as an indicator of performance of the cardiovascular system. The heart rate replaces the %V O2max in exercise program prescription to improve aerobic endurance. In order to achieve an optimal effect during endurance training, the athlete needs to work out at a heart rate high enough to trigger the aerobic metabolism, while avoiding the high heart rates that bring along significant risks of myocardial infarction. The minimal and optimal base training programs, followed by stretching exercises to prevent injuries, are adequate programs to maximize benefits and minimize health risks for the cardiovascular system during single session training. In this thesis, we have defined an ambient intelligence system functional model that monitors, evaluates and trains physical qualities, and it has been validated for aerobic endurance. It is based on the Android System and the “GOW Running” smart shirt. The system has been evaluated during functional assessment stress testing of aerobic endurance in the Stress Physiology Laboratory (SPL) of the Technical University of Madrid (UPM). Furthermore, a voice system, designed to guide the user through minimal and optimal base training programs, has been evaluated. Also the software development has been evaluated. By means of user experience questionnaires, we have rated the attractiveness of the android application. Moreover, we have defined a methodology and a new kind of questionnaires in order to assess the user experience with the audio exercise guide system. The results obtained confirm the model. We have a high similarity between HR measurements made of our system and the one used by SPL. We have also a high correlation between the VO2max estimations of our system and the SPL system. All users, that tried the voice guidance system for minimal and optimal base training programs, were able to perform the 95% of the training session with an error lower than the 10% of theoretical maximum heart rate. The application appeared attractive to the users, and it has also been proven that the voice guidance system was useful. As result we obtained a positive evaluation of the users' satisfaction while they interacted with the system. In conclusion, it has been demonstrated that is possible to develop mobile Ambient Intelligence applications for the improvement of healthy lifestyle. AmIRTEM model is the first theoretical reference functional model for the design of this kind of applications. Further studies will be realized in order to extend the AmIRTEM model to other physical qualities whose physiological models are more complex than the aerobic endurance.

A dual-band priority assignment algorithm for dynamic QoS resource management

Future high-quality consumer electronics will contain a number of applications running in a highly dynamic environment, and their execution will need to be efficiently arbitrated by the underlying platform software. The multimedia applications that currently execute in such similar contexts face frequent run-time variations in their resource demands, originated by the greedy nature of the multimedia processing itself. Changes in resource demands are triggered by numerous reasons (e.g. a switch in the input media compression format). Such situations require real-time adaptation mechanisms to adjust the system operation to the new requirements, and this must be done seamlessly to satisfy the user experience. One solution for efficiently managing application execution is to apply quality of service resource management techniques, based on assigning and enforcing resource contracts to applications. Most resource management solutions provide temporal isolation by enforcing resource assignments and avoiding any resource overruns. However, this has a clear limitation over the cost-effective resource usage. This paper presents a simple priority assignment scheme based on uniform priority bands to allow that greedy multimedia tasks incur in safe overruns that increase resource usage and do not threaten the timely execution of non-overrunning tasks. Experimental results show that the proposed priority assignment scheme in combination with a resource accounting mechanism preserves timely multimedia execution and delivery, achieves a higher cost-effective processor usage, and guarantees the execution isolation of non-overrunning tasks.

Mobile application stores: success factors, existing approaches and future developments

The mobile user experience has been significantly altered with the arrival of mobile broadband widespread deployments, massive improvements in available smartphones, and a shift in user habits toward a more participative, communicative role. In this context, mobile application stores have revolutionized software and content delivery. These stores focus on the applications, building around them an ecosystem of developers and consumers. The store greatly lessens the barrier between these agents, providing significant benefits to both developers and consumers. In this article we analyze this phenomenon, describing its originating factors and fundamental characteristics. We also perform a more detailed study on the two most successful application stores, identifying different approaches to implementing the model.

Integración del descodificador OpenSVC en el DSP del OMAP3530

Hoy en día el uso de dispositivos portátiles multimedia es ya una realidad totalmente habitual. Además, estos dispositivos tienen una capacidad de cálculo y unos recursos gráficos y de memoria altos, tanto es así que por ejemplo en un móvil se pueden reproducir vídeos de muy alta calidad o tener capacidad para manejar entornos 3D. El precio del uso de estos recursos es un mayor consumo de batería que en ocasiones es demasiado alto y acortan en gran medida la vida de la carga útil de la batería. El Grupo de Diseño Electrónico y Microelectrónico de la Universidad Politécnica de Madrid ha abierto una línea de trabajo que busca la optimización del consumo de energía en este tipo de dispositivos, concretamente en el ámbito de la reproducción de vídeo. El enfoque para afrontar la solución del problema se basa en obtener un mayor rendimiento de la batería a costa de disminuir la experiencia multimedia del usuario. De esta manera, cuando la carga de la batería esté por debajo de un determinado umbral mientras el dispositivo esté reproduciendo un vídeo de alta calidad será el dispositivo quien se autoconfigure dinámicamente para consumir menos potencia en esta tarea, reduciendo la tasa de imágenes por segundo o la resolución del vídeo que se descodifica. Además de lo citado anteriormente se propone dividir la descodificación y la representación del vídeo en dos procesadores, uno de propósito general y otro para procesado digital de señal, con esto se consigue que tener la misma capacidad de cálculo que con un solo procesador pero a una frecuencia menor. Para materializar la propuesta se usará la tarjeta BeagleBoard basada en un procesador multinúcleo OMAP3530 de Texas Instrument que contiene dos núcleos: un ARM1 Cortex-A8 y un DSP2 de la familia C6000. Este procesador multinúcleo además permite modificar la frecuencia de reloj y la tensión de alimentación dinámicamente para conseguir reducir de este modo el consumo del terminal. Por otro lado, como reproductor de vídeos se utilizará una versión de MPlayer que integra un descodificador de vídeo escalable que permite elegir dinámicamente la resolución o las imágenes por segundo que se decodifican para posteriormente mostrarlas. Este reproductor se ejecutará en el núcleo ARM pero debido a la alta carga computacional de la descodificación de vídeos, y que el ARM no está optimizado para este tipo de procesado de datos, el reproductor debe encargar la tarea de la descodificación al DSP. El objetivo de este Proyecto Fin de Carrera consiste en que mientras el descodificador de vídeo está ejecutándose en el núcleo DSP y el Mplayer en el núcleo ARM del OMAP3530 se pueda elegir dinámicamente qué parte del vídeo se descodifica, es decir, seleccionar en tiempo real la calidad o capa del vídeo que se quiere mostrar. Haciendo esto, se podrá quitar carga computacional al núcleo ARM y asignársela al DSP el cuál puede procesarla a menor frecuencia para ahorrar batería. 1 ARM: Es una arquitectura de procesadores de propósito general basada en RISC (Reduced Instruction Set Computer). Es desarrollada por la empresa inglesa ARM holdings. 2 DSP: Procesador Digital de Señal (Digital Signal Processor). Es un sistema basado en procesador, el cual está orientado al cálculo matemático a altas velocidad. Generalmente poseen varias unidades aritmético-lógicas (ALUs) para conseguir realizar varias operaciones simultáneamente. SUMMARY. Nowadays, the use of multimedia devices is a well known reality. In addition, these devices have high graphics and calculus performance and a lot of memory as well. In instance, we can play high quality videos and 3D environments in a mobile phone. That kind of use may increase the device's power consumption and make shorter the battery duration. Electronic and Microelectronic Design Group of Technical University of Madrid has a research line which is looking for optimization of power consumption while these devices are playing videos. The solution of this trouble is based on taking more advantage of battery by decreasing multimedia user experience. On this way, when battery charge is under a threshold while device is playing a high quality video the device is going to configure itself dynamically in order to decrease its power consumption by decreasing frame per second rate, video resolution or increasing the noise in the decoded frame. It is proposed splitting decoding and representation tasks in two processors in order to have the same calculus capability with lower frecuency. The first one is specialized in digital signal processing and the other one is a general purpose processor. In order to materialize this proposal we will use a board called BeagleBoard which is based on a multicore processor called OMAP3530 from Texas Instrument. This processor includes two cores: ARM Cortex-A8 and a TMS320C64+ DSP core. Changing clock frequency and supply voltage is allowed by OMAP3530, we can decrease the power consumption on this way. On the other hand, MPlayer will be used as video player. It includes a scalable video decoder which let us changing dynamically the resolution or frames per second rate of the video in order to show it later. This player will be executed by ARM core but this is not optimized for this task, for that reason, DSP core will be used to decoding video. The target of this final career project is being able to choose which part of the video is decoded each moment while decoder is executed by DSP and Mplayer by ARM. It will be able to change in real time the video quality, resolution and frames per second that user want to show. On this way, reducing the computational charge within the processor will be possible.

Contribution to proactivity in mobile context-aware recommender systems

Los sistemas de recomendación son potentes herramientas de filtrado de información que permiten a usuarios solicitar sugerencias sobre ítems que cubran sus necesidades. Tradicionalmente estas recomendaciones han estado basadas en opiniones de los mismos, así como en datos obtenidos de su consumo histórico o comportamiento en el propio sistema. Sin embargo, debido a la gran penetración y uso de los dispositivos móviles en nuestra sociedad, han surgido nuevas oportunidades en el campo de los sistemas de recomendación móviles gracias a la información contextual que se puede obtener sobre la localización o actividad de los usuarios. Debido a este estilo de vida en el que todo tiende a la movilidad y donde los usuarios están plenamente interconectados, la información contextual no sólo es física, sino que también adquiere una dimensión social. Todo esto ha dado lugar a una nueva área de investigación relacionada con los Sistemas de Recomendación Basados en Contexto (CARS) móviles donde se busca incrementar el nivel de personalización de las recomendaciones al usar dicha información. Por otro lado, este nuevo escenario en el que los usuarios llevan en todo momento un terminal móvil consigo abre la puerta a nuevas formas de recomendar. Sustituir el tradicional patrón de uso basado en petición-respuesta para evolucionar hacia un sistema proactivo es ahora posible. Estos sistemas deben identificar el momento más adecuado para generar una recomendación sin una petición explícita del usuario, siendo para ello necesario analizar su contexto. Esta tesis doctoral propone un conjunto de modelos, algoritmos y métodos orientados a incorporar proactividad en CARS móviles, a la vez que se estudia el impacto que este tipo de recomendaciones tienen en la experiencia de usuario con el fin de extraer importantes conclusiones sobre "qué", "cuándo" y "cómo" se debe notificar proactivamente. Con este propósito, se comienza planteando una arquitectura general para construir CARS móviles en escenarios sociales. Adicionalmente, se propone una nueva forma de representar el proceso de recomendación a través de una interfaz REST, lo que permite crear una arquitectura independiente de dispositivo y plataforma. Los detalles de su implementación tras su puesta en marcha en el entorno bancario español permiten asimismo validar el sistema construido. Tras esto se presenta un novedoso modelo para incorporar proactividad en CARS móviles. Éste muestra las ideas principales que permiten analizar una situación para decidir cuándo es apropiada una recomendación proactiva. Para ello se presentan algoritmos que establecen relaciones entre lo propicia que es una situación y cómo esto influye en los elementos a recomendar. Asimismo, para demostrar la viabilidad de este modelo se describe su aplicación a un escenario de recomendación para herramientas de creación de contenidos educativos. Siguiendo el modelo anterior, se presenta el diseño e implementación de nuevos interfaces móviles de usuario para recomendaciones proactivas, así como los resultados de su evaluación entre usuarios, lo que aportó importantes conclusiones para identificar cuáles son los factores más relevantes a considerar en el diseño de sistemas proactivos. A raíz de los resultados anteriores, el último punto de esta tesis presenta una metodología para calcular cuán apropiada es una situación de cara a recomendar de manera proactiva siguiendo el modelo propuesto. Como conclusión, se describe la validación llevada a cabo tras la aplicación de la arquitectura, modelo de recomendación y métodos descritos en este trabajo en una red social de aprendizaje europea. Finalmente, esta tesis discute las conclusiones obtenidas a lo largo de la extensa investigación llevada a cabo, y que ha propiciado la consecución de una buena base teórica y práctica para la creación de sistemas de recomendación móviles proactivos basados en información contextual. ABSTRACT Recommender systems are powerful information filtering tools which offer users personalized suggestions about items whose aim is to satisfy their needs. Traditionally the information used to make recommendations has been based on users’ ratings or data on the item’s consumption history and transactions carried out in the system. However, due to the remarkable growth in mobile devices in our society, new opportunities have arisen to improve these systems by implementing them in ubiquitous environments which provide rich context-awareness information on their location or current activity. Because of this current all-mobile lifestyle, users are socially connected permanently, which allows their context to be enhanced not only with physical information, but also with a social dimension. As a result of these novel contextual data sources, the advent of mobile Context-Aware Recommender Systems (CARS) as a research area has appeared to improve the level of personalization in recommendation. On the other hand, this new scenario in which users have their mobile devices with them all the time offers the possibility of looking into new ways of making recommendations. Evolving the traditional user request-response pattern to a proactive approach is now possible as a result of this rich contextual scenario. Thus, the key idea is that recommendations are made to the user when the current situation is appropriate, attending to the available contextual information without an explicit user request being necessary. This dissertation proposes a set of models, algorithms and methods to incorporate proactivity into mobile CARS, while the impact of proactivity is studied in terms of user experience to extract significant outcomes as to "what", "when" and "how" proactive recommendations have to be notified to users. To this end, the development of this dissertation starts from the proposal of a general architecture for building mobile CARS in scenarios with rich social data along with a new way of managing a recommendation process through a REST interface to make this architecture multi-device and cross-platform compatible. Details as regards its implementation and evaluation in a Spanish banking scenario are provided to validate its usefulness and user acceptance. After that, a novel model is presented for proactivity in mobile CARS which shows the key ideas related to decide when a situation warrants a proactive recommendation by establishing algorithms that represent the relationship between the appropriateness of a situation and the suitability of the candidate items to be recommended. A validation of these ideas in the area of e-learning authoring tools is also presented. Following the previous model, this dissertation presents the design and implementation of new mobile user interfaces for proactive notifications. The results of an evaluation among users testing these novel interfaces is also shown to study the impact of proactivity in the user experience of mobile CARS, while significant factors associated to proactivity are also identified. The last stage of this dissertation merges the previous outcomes to design a new methodology to calculate the appropriateness of a situation so as to incorporate proactivity into mobile CARS. Additionally, this work provides details about its validation in a European e-learning social network in which the whole architecture and proactive recommendation model together with its methods have been implemented. Finally, this dissertation opens up a discussion about the conclusions obtained throughout this research, resulting in useful information from the different design and implementation stages of proactive mobile CARS.

Case study on mobile applications UX: effect of the usage of a crosss-platform development framework

Cross-platform development frameworks for mobile applications promise important advantages in cost cuttings and easy maintenance, posing as a very good option for organizations interested in the design of mobile applications for several platforms. Given that platform conventions are especially important for the User eXperience (UX) of mobile applications, the usage of framework where the same code defines the behavior of the app in different platforms could have negative impact in the UX. The objetive of this study is comparing the cross-platform and the native approach for being able to determine if the selected development approach has any impact on the users in terms of UX. To be able to set a base line under this subject, study on cross-platform frameworks was performed to select the most appropriate one from a UX point of view. In order to achieve the objectives of this work, two development teams have developed two versions of the same application; one using framework that generates Android and iOS versions automatically, and another team developing native versions of the same application. The alternative versions for each platform have been evaluated with 37 users with a combination of a laboratory usability test and a longitudinal study. The results show that differences are minimal in the Android version, but in iOS, even if a reasonable good UX can be obtained with the usage of this framework by an UX-conscious design team, a higher level of UX can be obtained directly developing in native code.

Energy-based Fair Queuing: Energy-centric Processor Scheduling Algorithm for Battery-limited Mobile Systems

Los dispositivos móviles modernos disponen cada vez de más funcionalidad debido al rápido avance de las tecnologías de las comunicaciones y computaciones móviles. Sin embargo, la capacidad de la batería no ha experimentado un aumento equivalente. Por ello, la experiencia de usuario en los sistemas móviles modernos se ve muy afectada por la vida de la batería, que es un factor inestable de difícil de control. Para abordar este problema, investigaciones anteriores han propuesto un esquema de gestion del consumo (PM) centrada en la energía y que proporciona una garantía sobre la vida operativa de la batería mediante la gestión de la energía como un recurso de primera clase en el sistema. Como el planificador juega un papel fundamental en la administración del consumo de energía y en la garantía del rendimiento de las aplicaciones, esta tesis explora la optimización de la experiencia de usuario para sistemas móviles con energía limitada desde la perspectiva de un planificador que tiene en cuenta el consumo de energía en un contexto en el que ésta es un recurso de primera clase. En esta tesis se analiza en primer lugar los factores que contribuyen de forma general a la experiencia de usuario en un sistema móvil. Después se determinan los requisitos esenciales que afectan a la experiencia de usuario en la planificación centrada en el consumo de energía, que son el reparto proporcional de la potencia, el cumplimiento de las restricciones temporales, y cuando sea necesario, el compromiso entre la cuota de potencia y las restricciones temporales. Para cumplir con los requisitos, el algoritmo clásico de fair queueing y su modelo de referencia se extienden desde los dominios de las comunicaciones y ancho de banda de CPU hacia el dominio de la energía, y en base a ésto, se propone el algoritmo energy-based fair queueing (EFQ) para proporcionar una planificación basada en la energía. El algoritmo EFQ está diseñado para compartir la potencia consumida entre las tareas mediante su planificación en función de la energía consumida y de la cuota reservada. La cuota de consumo de cada tarea con restricciones temporales está protegida frente a diversos cambios que puedan ocurrir en el sistema. Además, para dar mejor soporte a las tareas en tiempo real y multimedia, se propone un mecanismo para combinar con el algoritmo EFQ para dar preferencia en la planificación durante breves intervalos de tiempo a las tareas más urgentes con restricciones temporales.Las propiedades del algoritmo EFQ se evaluan a través del modelado de alto nivel y la simulación. Los resultados de las simulaciones indican que los requisitos esenciales de la planificación centrada en la energía pueden lograrse. El algoritmo EFQ se implementa más tarde en el kernel de Linux. Para evaluar las propiedades del planificador EFQ basado en Linux, se desarrolló un banco de pruebas experimental basado en una sitema empotrado, un programa de banco de pruebas multihilo, y un conjunto de pruebas de código abierto. A través de experimentos específicamente diseñados, esta tesis verifica primero las propiedades de EFQ en la gestión de la cuota de consumo de potencia y la planificación en tiempo real y, a continuación, explora los beneficios potenciales de emplear la planificación EFQ en la optimización de la experiencia de usuario para sistemas móviles con energía limitada. Los resultados experimentales sobre la gestión de la cuota de energía muestran que EFQ es más eficaz que el planificador de Linux-CFS en la gestión de energía, logrando un reparto proporcional de la energía del sistema independientemente de en qué dispositivo se consume la energía. Los resultados experimentales en la planificación en tiempo real demuestran que EFQ puede lograr de forma eficaz, flexible y robusta el cumplimiento de las restricciones temporales aunque se dé el caso de aumento del el número de tareas o del error en la estimación de energía. Por último, un análisis comparativo de los resultados experimentales sobre la optimización de la experiencia del usuario demuestra que, primero, EFQ es más eficaz y flexible que los algoritmos tradicionales de planificación del procesador, como el que se encuentra por defecto en el planificador de Linux y, segundo, que proporciona la posibilidad de optimizar y preservar la experiencia de usuario para los sistemas móviles con energía limitada. Abstract Modern mobiledevices have been becoming increasingly powerful in functionality and entertainment as the next-generation mobile computing and communication technologies are rapidly advanced. However, the battery capacity has not experienced anequivalent increase. The user experience of modern mobile systems is therefore greatly affected by the battery lifetime,which is an unstable factor that is hard to control. To address this problem, previous works proposed energy-centric power management (PM) schemes to provide strong guarantee on the battery lifetime by globally managing energy as the first-class resource in the system. As the processor scheduler plays a pivotal role in power management and application performance guarantee, this thesis explores the user experience optimization of energy-limited mobile systemsfrom the perspective of energy-centric processor scheduling in an energy-centric context. This thesis first analyzes the general contributing factors of the mobile system user experience.Then itdetermines the essential requirements on the energy-centric processor scheduling for user experience optimization, which are proportional power sharing, time-constraint compliance, and when necessary, a tradeoff between the power share and the time-constraint compliance. To meet the requirements, the classical fair queuing algorithm and its reference model are extended from the network and CPU bandwidth sharing domain to the energy sharing domain, and based on that, the energy-based fair queuing (EFQ) algorithm is proposed for performing energy-centric processor scheduling. The EFQ algorithm is designed to provide proportional power shares to tasks by scheduling the tasks based on their energy consumption and weights. The power share of each time-sensitive task is protected upon the change of the scheduling environment to guarantee a stable performance, and any instantaneous power share that is overly allocated to one time-sensitive task can be fairly re-allocated to the other tasks. In addition, to better support real-time and multimedia scheduling, certain real-time friendly mechanism is combined into the EFQ algorithm to give time-limited scheduling preference to the time-sensitive tasks. Through high-level modelling and simulation, the properties of the EFQ algorithm are evaluated. The simulation results indicate that the essential requirements of energy-centric processor scheduling can be achieved. The EFQ algorithm is later implemented in the Linux kernel. To assess the properties of the Linux-based EFQ scheduler, an experimental test-bench based on an embedded platform, a multithreading test-bench program, and an open-source benchmark suite is developed. Through specifically-designed experiments, this thesis first verifies the properties of EFQ in power share management and real-time scheduling, and then, explores the potential benefits of employing EFQ scheduling in the user experience optimization for energy-limited mobile systems. Experimental results on power share management show that EFQ is more effective than the Linux-CFS scheduler in managing power shares and it can achieve a proportional sharing of the system power regardless of on which device the energy is spent. Experimental results on real-time scheduling demonstrate that EFQ can achieve effective, flexible and robust time-constraint compliance upon the increase of energy estimation error and task number. Finally, a comparative analysis of the experimental results on user experience optimization demonstrates that EFQ is more effective and flexible than traditional processor scheduling algorithms, such as those of the default Linux scheduler, in optimizing and preserving the user experience of energy-limited mobile systems.

A case study on cross-platform development frameworks for mobile applications and UX

Cross-platform development frameworks for mobile applications promise important advantages in cost cuttings and easy maintenance, posing as a very good option for organizations interested in the design of mobile applications for several platforms. Given that platform conventions are especially important for the User eXperience (UX) of mobile applications, the usage of a framework where the same code defines the behavior of the app in different platforms could have a negative impact in the UX. This paper describes a study where two independent teams have designed two different versions of a mobile application, one using a framework that generates Android and iOS versions automatically, and another team using native tools. The alternative versions for each platform have been evaluated with 37 users with a combination of a laboratory usability test and a longitudinal study. The results show that differences are minimal in the Android platform, but in iOS, even if a reasonably good UX can be obtained with the usage of this framework by an UX-conscious design team, a higher level of UX can be obtained directly developing with a native tool.

Software architecture implementation based on OpenSim

One of the objectives of the European Higher Education Area is the promotion of collaborative and informal learning through the implementation of educational practices. 3D virtual environments become an ideal space for such activities. On the other hand, the problem of financing in Spanish universities has led to the search for new ways to optimize available resources. The Technical University of Madrid requires the use of laboratories which due to their dangerousness, duration or control of the developed processes are difficult to perform in real life. For this reason, we have developed several 3D laboratories in virtual environment. The laboratories are built on open source platform OpenSim. In this paper it is exposed the use of the OpenSim platform for these new teaching experiences and the new design of the software architecture. This architecture requires the adaptation of the platform to the needs of the users and the different laboratories of our University. We will explain the structure of the implemented architecture and the process of creating and configuring it. The proposed architecture is decentralized, each laboratory is housed in different an educational center. The architecture adds several services, among others, the creation and management of users automated, communication between external services and platforms in different program languages. Therefore, we achieve improving the user experience and rising the functionalities of laboratories.