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.

An attitude-based reasoning strategy to enhance interaction with augmented objects

This paper describes a mobile-based system to interact with objects in smart spaces, where the offer of resources may be extensive. The underlying idea is to use the augmentation capabilities of the mobile device to enable it as user-object mediator. In particular, the paper details how to build an attitude-based reasoning strategy that facilitates user-object interaction and resource filtering. The strategy prioritizes the available resources depending on the spatial history of the user, his real-time location and orientation and, finally, his active touch and focus interactions with the virtual overlay. The proposed reasoning method has been partially validated through a prototype that handles 2D and 3D visualization interfaces. This framework makes possible to develop in practice the IoT paradigm, augmenting the objects without physically modifying them.

Smart Spaces and Smart Objects interoperability Architecture (S3OiA)

The presented work aims to contribute towards the standardization and the interoperability off the Future Internet through an open and scalable architecture design. We present S³OiA as a syntactic/semantic Service-Oriented Architecture that allows the integration of any type of object or device, not mattering their nature, on the Internet of Things. Moreover, the architecture makes possible the use of underlying heterogeneous resources as a substrate for the automatic composition of complex applications through a semantic Triple Space paradigm. Created applications are dynamic and adaptive since they are able to evolve depending on the context where they are executed. The validation scenario of this architecture encompasses areas which are prone to involve human beings in order to promote personal autonomy, such as home-care automation environments and Ambient Assisted Living.

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.

NFC based remote control of services for interactive spaces

Ubiquitous computing (one person, many computers) is the third era in the history of computing. It follows the mainframe era (many people, one computer) and the PC era (one person, one computer). Ubiquitous computing empowers people to communicate with services by interacting with their surroundings. Most of these so called smart environments contain sensors sensing users’ actions and try to predict the users’ intentions and necessities based on sensor data. The main drawback of this approach is that the system might perform unexpected or unwanted actions, making the user feel out of control. In this master thesis we propose a different procedure based on Interactive Spaces: instead of predicting users’ intentions based on sensor data, the system reacts to users’ explicit predefined actions. To that end, we present REACHeS, a server platform which enables communication among services, resources and users located in the same environment. With REACHeS, a user controls services and resources by interacting with everyday life objects and using a mobile phone as a mediator between himself/herself, the system and the environment. REACHeS’ interfaces with a user are built upon NFC (Near Field Communication) technology. NFC tags are attached to objects in the environment. A tag stores commands that are sent to services when a user touches the tag with his/her NFC enabled device. The prototypes and usability tests presented in this thesis show the great potential of NFC to build such user interfaces.

WHERE2 location aided communications

This paper presents an overview of preliminary results of investigations within the WHERE2 Project on identifying promising avenues for location aided enhancements to wireless communication systems. The wide ranging contributions are organized according to the following targeted systems: cellular networks, mobile ad hoc networks (MANETs) and cognitive radio. Location based approaches are found to alleviate significant signaling overhead in various forms of modern communication paradigms that are very information hungry in terms of channel state information at the transmitter(s). And this at a reasonable cost given the ubiquitous availability of location information in recent wireless standards or smart phones. Location tracking furthermore opens the new perspective of slow fading prediction.

E-Flow: A communication system for user notification in dynamic evacuation scenarios

Most of the current evacuation plans are based on static signaling, fixed monitoring infrastructure, and limited user notification and feedback mechanisms. These facts lead to lower situation awareness, in the case event of an emergency, such as blocked emergency exits, while delaying the reaction time of individuals. In this context, we introduce the E-Flow communication system, which improves the user awareness by integrating personal, mobile and fixed devices with the existing monitoring infrastructure. Our system broadens the notification and monitoring alternatives, in real time, among, safety staff, end-users and evacuation related devices, such as sensors and actuators.

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.

CloudRoom: módulo de gestión de cursos online, abiertos y masivos

La razón de este proyecto, es la de desarrollar el módulo de cursos de la plataforma de Massive Online Open Courses (MOOCs), CloudRoom. Dicho módulo está englobado en una arquitectura orientada a servicios (SOA) y en una infraestructura de Cloud Computing utilizando Amazon Web Services (AWS). Nuestro objetivo es el de diseñar un Software as a Service (SaaS) robusto con las cualidades que a un producto de este tipo se le estiman: alta disponibilidad, alto rendimiento, gran experiencia de usuario y gran extensibilidad del sistema. Para lograrlo, se llevará a cabo la integración de las últimas tendencias tecnológicas dentro del desarrollo de sistemas distribuidos como Neo4j, Node.JS, Servicios RESTful, CoffeeScript. Todo esto siguiendo un estrategia de desarrollo PLAN-DO-CHECK utilizando Scrum y prácticas de metodologías ágiles. ---ABSTRACT---The reason of this Project is to develop the courses‟ module of CloudRoom, a Massive Online Open Courses platform. This module is encapsulated in a service-oriented architecture (SOA) based on a Cloud Computing infrastructure built on Amazon Web Services (AWS). Our goal is to design a robust Software as a Service (SaaS) with the qualities that are estimated in a product of this type: high availability, high performance, great user experience and great extensibility of the system. In order to address this, we carry out the integration of the latest technology trends in the development of distributed systems: Neo4j, Node.JS, RESTful Services and CoffeeScript. All of this, following a development strategy PLAN-DO-CHECK, using Scrum and practices of agile methodologies.

Análisis de usabilidad y aplicación de los resultados en el desarrollo de plataformas web

Este trabajo trata cómo se pueden aplicar las técnicas de análisis de usabilidad al desarrollo de plataformas web. Actualmente es común que los servicios sean ofrecidos mediante plataformas web para un grupo muy heterogéneo de personas. Por otra parte, los análisis de usabilidad son una herramienta muy útil para conocer cómo interactúan las personas con los ordenadores y mejorar el diseño de las aplicaciones. Realizar un buen diseño permite mejorar la experiencia de usuario, factor fundamental para el éxito de cualquier producto que requiera interacción con el usuario. A continuación se describen las diferentes fases de los test de usabilidad y se detalla cómo han sido aplicadas durante el desarrollo del proyecto. Finalmente, se presentarán los resultados obtenidos durante la evaluación de la plataforma y el análisis de los mismos indicando cómo han afectado al diseño de la plataforma. ---ABSTRACT---This document discusses how to apply usability test techniques over web platform development. Nowadays, it is common that services are offered through web platforms for a large group of heterogeneous people. Moreover, usability tests are a very useful tool to understand human-computer interaction and improve the design of the applications. A good design can improve user experience, which is essential for the success of any product that requires user interaction. The following pages describes the different phases of usability testing and detail how these have been applied during the development of the project. Finally, the results obtained during the platform evaluation are presented and analysed, explaining how they have affected the design of the platform.

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.

Personalisation of intelligent homecare services adapted to children with motor impairments

Ambient Intelligence could support innovative application domains like motor impairments' detection at the home environment. This research aims to prevent neurodevelopmental disorders through the natural interaction of the children with embedded intelligence daily life objects, like home furniture and toys. Designed system uses an interoperable platform to provide two intelligent interrelated home healthcare services: monitoring of children¿s abilities and completion of early stimulation activities. A set of sensors, which are embedded within the rooms, toys and furniture, allows private data gathering about the child's interaction with the environment. This information feeds a reasoning subsystem, which encloses an ontology of neurodevelopment items, and adapts the service to the age and acquisition of expected abilities. Next, the platform proposes customized stimulation services by taking advantage of the existing facilities at the child's environment. The result integrates Embedded Sensor Systems for Health at Mälardalen University with UPM Smart Home, for adapted services delivery.

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.

Mining mobile apps reviews to support release planning

The mobile apps market is a tremendous success, with millions of apps downloaded and used every day by users spread all around the world. For apps’ developers, having their apps published on one of the major app stores (e.g. Google Play market) is just the beginning of the apps lifecycle. Indeed, in order to successfully compete with the other apps in the market, an app has to be updated frequently by adding new attractive features and by fixing existing bugs. Clearly, any developer interested in increasing the success of her app should try to implement features desired by the app’s users and to fix bugs affecting the user experience of many of them. A precious source of information to decide how to collect users’ opinions and wishes is represented by the reviews left by users on the store from which they downloaded the app. However, to exploit such information the app’s developer should manually read each user review and verify if it contains useful information (e.g. suggestions for new features). This is something not doable if the app receives hundreds of reviews per day, as happens for the very popular apps on the market. In this work, our aim is to provide support to mobile apps developers by proposing a novel approach exploiting data mining, natural language processing, machine learning, and clustering techniques in order to classify the user reviews on the basis of the information they contain (e.g. useless, suggestion for new features, bugs reporting). Such an approach has been empirically evaluated and made available in a web-­‐based tool publicly available to all apps’ developers. The achieved results showed that the developed tool: (i) is able to correctly categorise user reviews on the basis of their content (e.g. isolating those reporting bugs) with 78% of accuracy, (ii) produces clusters of reviews (e.g. groups together reviews indicating exactly the same bug to be fixed) that are meaningful from a developer’s point-­‐of-­‐view, and (iii) is considered useful by a software company working in the mobile apps’ development market.