Enabling technologies and cyber-physical systems for mission-critical scenarios

Programa Oficial de Doutoramento en Tecnoloxías da Información e Comunicacións en Redes Móbiles . 5029P01[Abstract] Reliable transport systems, defense, public safety and quality assurance in the Industry 4.0 are essential in a modern society. In a mission-critical scenario, a mission failure would jeopardize human lives and put at risk some other assets whose impairment or loss would significantly harm society or business results. Even small degradations of the communications supporting the mission could have large and possibly dire consequences. On the one hand, mission-critical organizations wish to utilize the most modern, disruptive and innovative communication systems and technologies, and yet, on the other hand, need to comply with strict requirements, which are very different to those of non critical scenarios. The aim of this thesis is to assess the feasibility of applying emerging technologies like Internet of Things (IoT), Cyber-Physical Systems (CPS) and 4G broadband communications in mission-critical scenarios along three key critical infrastructure sectors: transportation, defense and public safety, and shipbuilding. Regarding the transport sector, this thesis provides an understanding of the progress of communications technologies used for railways since the implantation of Global System for Mobile communications-Railways (GSM-R). The aim of this work is to envision the potential contribution of Long Term Evolution (LTE) to provide additional features that GSM-R would never support. Furthermore, the ability of Industrial IoT for revolutionizing the railway industry and confront today's challenges is presented. Moreover, a detailed review of the most common flaws found in Radio Frequency IDentification (RFID) based IoT systems is presented, including the latest attacks described in the literature. As a result, a novel methodology for auditing security and reverse engineering RFID communications in transport applications is introduced. The second sector selected is driven by new operational needs and the challenges that arise from modern military deployments. The strategic advantages of 4G broadband technologies massively deployed in civil scenarios are examined. Furthermore, this thesis analyzes the great potential for applying IoT technologies to revolutionize modern warfare and provide benefits similar to those in industry. It identifies scenarios where defense and public safety could leverage better commercial IoT capabilities to deliver greater survivability to the warfighter or first responders, while reducing costs and increasing operation efficiency and effectiveness. The last part is devoted to the shipbuilding industry. After defining the novel concept of Shipyard 4.0, how a shipyard pipe workshop works and what are the requirements for building a smart pipe system are described in detail. Furthermore, the foundations for enabling an affordable CPS for Shipyards 4.0 are presented. The CPS proposed consists of a network of beacons that continuously collect information about the location of the pipes. Its design allows shipyards to obtain more information on the pipes and to make better use of it. Moreover, it is indicated how to build a positioning system from scratch in an environment as harsh in terms of communications as a shipyard, showing an example of its architecture and implementation.[Resumen] En la sociedad moderna, los sistemas de transporte fiables, la defensa, la seguridad pública y el control de la calidad en la Industria 4.0 son esenciales. En un escenario de misión crítica, el fracaso de una misión pone en peligro vidas humanas y en riesgo otros activos cuyo deterioro o pérdida perjudicaría significativamente a la sociedad o a los resultados de una empresa. Incluso pequeñas degradaciones en las comunicaciones que apoyan la misión podrían tener importantes y posiblemente terribles consecuencias. Por un lado, las organizaciones de misión crítica desean utilizar los sistemas y tecnologías de comunicación más modernos, disruptivos e innovadores y, sin embargo, deben cumplir requisitos estrictos que son muy diferentes a los relativos a escenarios no críticos. El objetivo principal de esta tesis es evaluar la viabilidad de aplicar tecnologías emergentes como Internet of Things (IoT), Cyber-Physical Systems (CPS) y comunicaciones de banda ancha 4G en escenarios de misión crítica en tres sectores clave de infraestructura crítica: transporte, defensa y seguridad pública, y construcción naval. Respecto al sector del transporte, esta tesis permite comprender el progreso de las tecnologías de comunicación en el ámbito ferroviario desde la implantación de Global System for Mobile communications-Railway (GSM-R). El objetivo de este trabajo es analizar la contribución potencial de Long Term Evolution (LTE) para proporcionar características adicionales que GSM-R nunca podría soportar. Además, se presenta la capacidad de la IoT industrial para revolucionar la industria ferroviaria y afrontar los retos actuales. Asimismo, se estudian con detalle las vulnerabilidades más comunes de los sistemas IoT basados en Radio Frequency IDentification (RFID), incluyendo los últimos ataques descritos en la literatura. Como resultado, se presenta una metodología innovadora para realizar auditorías de seguridad e ingeniería inversa de las comunicaciones RFID en aplicaciones de transporte. El segundo sector elegido viene impulsado por las nuevas necesidades operacionales y los desafíos que surgen de los despliegues militares modernos. Para afrontarlos, se analizan las ventajas estratégicas de las tecnologías de banda ancha 4G masivamente desplegadas en escenarios civiles. Asimismo, esta tesis analiza el gran potencial de aplicación de las tecnologías IoT para revolucionar la guerra moderna y proporcionar beneficios similares a los alcanzados por la industria. Se identifican escenarios en los que la defensa y la seguridad pública podrían aprovechar mejor las capacidades comerciales de IoT para ofrecer una mayor capacidad de supervivencia al combatiente o a los servicios de emergencias, a la vez que reduce los costes y aumenta la eficiencia y efectividad de las operaciones. La última parte se dedica a la industria de construcción naval. Después de definir el novedoso concepto de Astillero 4.0, se describe en detalle cómo funciona el taller de tubería de astillero y cuáles son los requisitos para construir un sistema de tuberías inteligentes. Además, se presentan los fundamentos para posibilitar un CPS asequible para Astilleros 4.0. El CPS propuesto consiste en una red de balizas que continuamente recogen información sobre la ubicación de las tuberías. Su diseño permite a los astilleros obtener más información sobre las tuberías y hacer un mejor uso de las mismas. Asimismo, se indica cómo construir un sistema de posicionamiento desde cero en un entorno tan hostil en términos de comunicaciones, mostrando un ejemplo de su arquitectura e implementación

Aspect oriented service composition for telecommunication applications

This PhD dissertation investigates how to overcome the negative effects of cross cutting concerns in the development of composite service applications. It proposes a combination of dynamic aspect oriented programming with a rules driven service composition mechanism. This combination allows very flexible utilization of aspects based on run-time data. The thesis contributes a join-point model and it integrates techniques for weaving and advice definition into the underlying composition language and execution engine. A particular focus of the thesis is telecommunication applications with their unique model for utilizing heterogeneous constituent services and their severe real-time requirements. Next to its primary use for modular implementation and flexible deployment of concerns in telecommunication applications, the dissertation discusses AOP as a feature for automated management and customization of service applications. The verification of the proposed solution contributes a detailed assessment of run-time performance, including a theoretical model of the AOP implementation. It allows predicting the performance of various alternative solutions. The proposed solution for combined AOP and service composition provides properties, which directly address challenges in pervasive computing and the Internet of things. Thus, this dissertation advances beyond the telecommunication domain with results applicable to various highly relevant technical developments

Beam scanning by liquid-crystal biasing in a modified SIW structure

A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

Experimental Evaluation of Growing and Pruning Hyper Basis Function Neural Networks Trained with Extended Information Filter

In this paper we test Extended Information Filter (EIF) for sequential training of Hyper Basis Function Neural Networks with growing and pruning ability (HBF-GP). The HBF neuron allows different scaling of input dimensions to provide better generalization property when dealing with complex nonlinear problems in engineering practice. The main intuition behind HBF is in generalization of Gaussian type of neuron that applies Mahalanobis-like distance as a distance metrics between input training sample and prototype vector. We exploit concept of neuron’s significance and allow growing and pruning of HBF neurons during sequential learning process. From engineer’s perspective, EIF is attractive for training of neural networks because it allows a designer to have scarce initial knowledge of the system/problem. Extensive experimental study shows that HBF neural network trained with EIF achieves same prediction error and compactness of network topology when compared to EKF, but without the need to know initial state uncertainty, which is its main advantage over EKF