Generadores ScalaCheck para property-based testing de programas Spark y Spark Streaming

En los últimos años hemos sido testigos de la expansión del paradigma big data a una velocidad vertiginosa. Los cambios en este campo, nos permiten ampliar las áreas a tratar; lo que a su vez implica una mayor complejidad de los sistemas software asociados a estas tareas, como sucede en sistemas de monitorización o en el Internet de las Cosas (Internet of Things). Asimismo, la necesidad de implementar programas cada vez robustos y eficientes, es decir, que permitan el cómputo de datos a mayor velocidad y de los se obtengan información relevante, ahorrando costes y tiempo, ha propiciado la necesidad cada vez mayor de herramientas que permitan evaluar estos programas. En este contexto, el presente proyecto se centra en extender la herramienta sscheck. Sscheck permite la generación de casos de prueba basados en propiedades de programas escritos en Spark y Spark Streaming. Estos lenguajes forman parte de un mismo marco de código abierto para la computación distribuida en clúster. Dado que las pruebas basadas en propiedades generan datos aleatorios, es difícil reproducir los problemas encontrados en una cierta sesion; por ello, la extensión se centrará en cargar y guardar casos de test en disco mediante el muestreo de datos desde colecciones mayores.

Diseño y desarrollo de un servicio big data en la nube para búsqueda, compartición de ficheros y data mining

En esta memoria se presenta el diseño y desarrollo de una aplicación en la nube destinada a la compartición de objetos y servicios. El desarrollo de esta aplicación surge dentro del proyecto de I+D+i, SITAC: Social Internet of Things – Apps by and for the Crowd ITEA 2 11020, que trata de crear una arquitectura integradora y un “ecosistema” que incluya plataformas, herramientas y metodologías para facilitar la conexión y cooperación de entidades de distinto tipo conectadas a la red bien sean sistemas, máquinas, dispositivos o personas con dispositivos móviles personales como tabletas o teléfonos móviles. El proyecto innovará mediante la utilización de un modelo inspirado en las redes sociales para facilitar y unificar las interacciones tanto entre personas como entre personas y dispositivos. En este contexto surge la necesidad de desarrollar una aplicación destinada a la compartición de recursos en la nube que pueden ser tanto lógicos como físicos, y que esté orientada al big data. Ésta será la aplicación presentada en este trabajo, el “Resource Sharing Center”, que ofrece un servicio web para el intercambio y compartición de contenido, y un motor de recomendaciones basado en las preferencias de los usuarios. Con este objetivo, se han usado tecnologías de despliegue en la nube, como Elastic Beanstalk (el PaaS de Amazon Web Services), S3 (el sistema de almacenamiento de Amazon Web Services), SimpleDB (base de datos NoSQL) y HTML5 con JavaScript y Twitter Bootstrap para el desarrollo del front-end, siendo Python y Node.js las tecnologías usadas en el back end, y habiendo contribuido a la mejora de herramientas de clustering sobre big data. Por último, y de cara a realizar el estudio sobre las pruebas de carga de la aplicación se ha usado la herramienta ApacheJMeter.

Arquitetura computacional para redes orgânicas e heterogêneas: plano de controle do sistema operacional swarm.

Computational Swarms (enxames computacionais), consistindo da integração de sensores e atuadores inteligentes no nosso mundo conectado, possibilitam uma extensão da info-esfera no mundo físico. Nós chamamos esta info-esfera extendida, cíber-física, de Swarm. Este trabalho propõe uma visão de Swarm onde dispositivos computacionais cooperam dinâmica e oportunisticamente, gerando redes orgânicas e heterogêneas. A tese apresenta uma arquitetura computacional do Plano de Controle do Sistema Operacional do Swarm, que é uma camada de software distribuída embarcada em todos os dispositivos que fazem parte do Swarm, responsável por gerenciar recursos, definindo atores, como descrever e utilizar serviços e recursos (como divulgá-los e descobrí-los, como realizar transações, adaptações de conteúdos e cooperação multiagentes). O projeto da arquitetura foi iniciado com uma revisão da caracterização do conceito de Swarm, revisitando a definição de termos e estabelecendo uma terminologia para ser utilizada. Requisitos e desafios foram identificados e uma visão operacional foi proposta. Esta visão operacional foi exercitada com casos de uso e os elementos arquiteturais foram extraídos dela e organizados em uma arquitetura. A arquitetura foi testada com os casos de uso, gerando revisões do sistema. Cada um dos elementos arquiteturais requereram revisões do estado da arte. Uma prova de conceito do Plano de Controle foi implementada e uma demonstração foi proposta e implementada. A demonstração selecionada foi o Smart Jukebox, que exercita os aspectos distribuídos e a dinamicidade do sistema proposto. Este trabalho apresenta a visão do Swarm computacional e apresenta uma plataforma aplicável na prática. A evolução desta arquitetura pode ser a base de uma rede global, heterogênea e orgânica de redes de dispositivos computacionais alavancando a integração de sistemas cíber-físicos na núvem permitindo a cooperação de sistemas escaláveis e flexíveis, interoperando para alcançar objetivos comuns.

Monitoring and Prevention the Smart Cities

Nowadays, the intensive use of Technology Information (TI) provide solutions to problems of the high population density, energy conservation and cities management. This produces a newest concept of the city, Smart City. But the inclusion of TI in the city brings associated new problems, specifically the generation of electromagnetic fields from the available and new technological infrastructures installed in the city that did not exist before. This new scenario produces a negative effect on a particular group of the society, as are the group of persons with electromagnetic hypersensitivity pathology. In this work we propose a system that would allow you to detect and prevent the continuous exposure to such electromagnetic fields, without the need to include more devices or infrastructure which would only worsen these effects. Through the use of the architecture itself and Smart City services, it is possible to infer the necessary knowledge to know the situation of the EMF radiation and thus allow users to avoid the areas of greatest conflict. This knowledge, not only allows us to get EMF current map of the city, but also allows you to generate predictions and detect future risk situations.

Smart Sentinel: Monitoring and Prevention System in the Smart Cities

Today, faced with the constant rise of the Smart cities around the world, there is an exponential increase of the use and deployment of information technologies in the cities. The intensive use of Information Technology (IT) in these ecosystems facilitates and improves the quality of life of citizens, but in these digital communities coexist individuals whose health is affected developing or increasing diseases such as electromagnetic hypersensitivity. In this paper we present a monitoring, detection and prevention system to help this group, through which it is reported the rates of electromagnetic radiation in certain areas, based on the information that the own Smart City gives us. This work provides a perfect platform for the generation of predictive models for detection of future states of risk for humans.

Comunicazioni basate su onde millimetriche per sistemi 5G

Le comunicazioni wireless di Quinta Generazione, le quali è assodato che vadano a ricoprire un ruolo chiave e centrale nel futuro delle comunicazioni mobili, hanno suscitato l’interesse e l’investigazione da parte delle maggiori organizzazioni ed enti di ricerca internazionali. Internet of Things, i cosiddetti Use Cases, gli indici KPI e le tecnologie candidate per lo sviluppo, sono tra gli altri, i maggiori aspetti su cui attualmente la ricerca pone la propria attenzione al fine di poter definire ed implementare la rete di Quinta Generazione. Non da meno, ricevono forte interesse anche una serie d’aspetti legati all’utilizzo delle elevate frequenze, in particolar modo le bande delle onde millimetriche, nello sviluppo delle comunicazioni per sistemi 5G. L’utilizzo delle onde millimetriche nel futuro delle comunicazioni mobili è ad oggi considerato il fulcro della ricerca per l’implementazione dell’ architettura di rete di Quinta Generazione. Lo sviluppo di comunicazioni basate sulle onde millimetriche per i sistemi 5G presentano sia delle opportunità ma anche importanti problematiche. Tra queste ultime, l’elevate attenuazioni registrate nelle bande delle onde millimetriche pongono severi limiti qualora si voglia stabilire una comunicazione a lungo raggio e tale è un aspetto critico che interesse fortemente i vari ambiti della ricerca per poter efficacemente porre le basi per il futuro della comunicazione mobile di Quinta Generazione.

Efficient Multi-hop Broadcast Data Dissemination in IoT and Smart Cities

Internet of Things (IoT) can be defined as a “network of networks” composed by billions of uniquely identified physical Smart Objects (SO), organized in an Internet-like structure. Smart Objects can be items equipped with sensors, consumer devices (e.g., smartphones, tablets, or wearable devices), and enterprise assets that are connected both to the Internet and to each others. The birth of the IoT, with its communications paradigms, can be considered as an enabling factor for the creation of the so-called Smart Cities. A Smart City uses Information and Communication Technologies (ICT) to enhance quality, performance and interactivity of urban services, ranging from traffic management and pollution monitoring to government services and energy management. This thesis is focused on multi-hop data dissemination within IoT and Smart Cities scenarios. The proposed multi-hop techniques, mostly based on probabilistic forwarding, have been used for different purposes: from the improvement of the performance of unicast protocols for Wireless Sensor Networks (WSNs) to the efficient data dissemination within Vehicular Ad-hoc NETworks (VANETs).

Efficient Data Management with Applications to IoT

The Internet of Things (IoT) consists of a worldwide “network of networks,” composed by billions of interconnected heterogeneous devices denoted as things or “Smart Objects” (SOs). Significant research efforts have been dedicated to port the experience gained in the design of the Internet to the IoT, with the goal of maximizing interoperability, using the Internet Protocol (IP) and designing specific protocols like the Constrained Application Protocol (CoAP), which have been widely accepted as drivers for the effective evolution of the IoT. This first wave of standardization can be considered successfully concluded and we can assume that communication with and between SOs is no longer an issue. At this time, to favor the widespread adoption of the IoT, it is crucial to provide mechanisms that facilitate IoT data management and the development of services enabling a real interaction with things. Several reference IoT scenarios have real-time or predictable latency requirements, dealing with billions of device collecting and sending an enormous quantity of data. These features create a new need for architectures specifically designed to handle this scenario, hear denoted as “Big Stream”. In this thesis a new Big Stream Listener-based Graph architecture is proposed. Another important step, is to build more applications around the Web model, bringing about the Web of Things (WoT). As several IoT testbeds have been focused on evaluating lower-layer communication aspects, this thesis proposes a new WoT Testbed aiming at allowing developers to work with a high level of abstraction, without worrying about low-level details. Finally, an innovative SOs-driven User Interface (UI) generation paradigm for mobile applications in heterogeneous IoT networks is proposed, to simplify interactions between users and things.

Legibility, privacy and creativity:linked data in a surveillance society

This paper looks at the issue of privacy and anonymity through the prism of Scott's concept of legibility i.e. the desire of the state to obtain an ever more accurate mapping of its domain and the actors in its domain. We argue that privacy was absent in village life in the past, and it has arisen as a temporary phenomenon arising from the lack of appropriate technology to make all life in the city legible. Cities have been the loci of creativity for the major part of human civilisation. There is something specific about the illegibility of cities which facilitates creativity and innovation. By providing the technology to catalogue and classify all objects and ideas around us, this leads to a consideration of semantic web technologies, Linked Data and the Internet of Things as unwittingly furthering this ever greater legibility. There is a danger that the over description of a domain will lead to a loss in creativity and innovation. We conclude by arguing that our prime concern must be to preserve illegibility because the survival of some form, any form, of civilisation depends upon it.

Sensing information modelling for smart city

Sensing technology is a key enabler of the Internet of Things (IoT) and could produce huge volume data to contribute the Big Data paradigm. Modelling of sensing information is an important and challenging topic, which influences essentially the quality of smart city systems. In this paper, the author discusses the relevant technologies and information modelling in the context of smart city and especially reports the investigation of how to model sensing and location information in order to support smart city development.

Computazione Embodied e Disembodied: Cloud-based IoT

La tesi esplora la co-esistenza di computazioni embodied e disembodied nei moderni sistemi software, adottando come caso di studio il recente trend che vede sempre più coesi e integrati sistemi per l'Internet of Things e sistemi Cloud-based. Si analizzano i principali modelli di comunicazione, protocolli di comunicazione e architetture situate. Inoltre si realizza una piattaforma IoT Middleware cloud-based per mostrare come la computazione possa essere distribuita lato embodied e disembodied.

Sensor IoT para monitorización de consumo de energía en continua

Hoy en día la mayor parte de los sensores de energía IoT (Internet of Things) están orientados a la medida de corriente alterna (AC). No son aptos para monitorizar equipos que no estén conectados a la red eléctrica (baterías, paneles fotovoltaicos, etc.) o que formen parte de otros equipos más grandes y que estén situados detrás del transformador (ej. aceleradores de cómputo en supercomputadores). El presente trabajo tiene como objetivo principal construir un sistema, con una instalación sencilla y reducida, que permita la monitorización de consumo de dispositivos conectados a corriente continua. Toda la información recogida será mostrada a través de una interfaz web, que nos permitirá observar los cambios en el consumo en tiempo real con un intervalo de actualización especificado por el usuario. Además el sistema será robusto, con bajo coste de implementación y permitirá una alta escalabilidad, ya que el objetivo del proyecto es que sea escalable a nivel de centro de datos o institución.

Semantic Stream Processing for IoT Devices in the Food Safety Domain

Postprint

Comparison between SensibleThings and Kaa platform

With the Internet of Things becoming more and more popular, and a prediction that there will be more than 50 million devices connected to the Internet in 2020, the quantity of IoT platforms on the market is rapidly growing. Facing so many platforms to choose, the object of this thesis is to give some suggestions for reference by performing a quantitative comparison between two platforms: SensibleThings and Kaa. These two platforms have difference architectures so may suitable in different scenes. The comparison includes some measurement and evaluation under two designed scenarios and a general contrast in theory. Two scenarios cover cases of message delivery between two endpoints at different rates and multiple endpoints pushing log data continually. The result of measurement together with the theoretical analysis draw out the following conclusion. SensibleThings platform is more suitable for simple and small-scale message delivery between endpoints, like home environment with few devices. And Kaa platform is more suitable for large-scale and complicated application for data collection and processing, like meteorology field with huge amount of sensors and data.

IoT Based Pain Management using Physiological Parameters

The continuous technology evaluation is benefiting our lives to a great extent. The evolution of Internet of things and deployment of wireless sensor networks is making it possible to have more connectivity between people and devices used extensively in our daily lives. Almost every discipline of daily life including health sector, transportation, agriculture etc. is benefiting from these technologies. There is a great potential of research and refinement of health sector as the current system is very often dependent on manual evaluations conducted by the clinicians. There is no automatic system for patient health monitoring and assessment which results to incomplete and less reliable heath information. Internet of things has a great potential to benefit health care applications by automated and remote assessment, monitoring and identification of diseases. Acute pain is the main cause of people visiting to hospitals. An automatic pain detection system based on internet of things with wireless devices can make the assessment and redemption significantly more efficient. The contribution of this research work is proposing pain assessment method based on physiological parameters. The physiological parameters chosen for this study are heart rate, electrocardiography, breathing rate and galvanic skin response. As a first step, the relation between these physiological parameters and acute pain experienced by the test persons is evaluated. The electrocardiography data collected from the test persons is analyzed to extract interbeat intervals. This evaluation clearly demonstrates specific patterns and trends in these parameters as a consequence of pain. This parametric behavior is then used to assess and identify the pain intensity by implementing machine learning algorithms. Support vector machines are used for classifying these parameters influenced by different pain intensities and classification results are achieved. The classification results with good accuracy rates between two and three levels of pain intensities shows clear indication of pain and the feasibility of this pain assessment method. An improved approach on the basis of this research work can be implemented by using both physiological parameters and electromyography data of facial muscles for classification.