14 research outputs found

    Computational Intelligence and Human- Computer Interaction: Modern Methods and Applications

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    The present book contains all of the articles that were accepted and published in the Special Issue of MDPI’s journal Mathematics titled "Computational Intelligence and Human–Computer Interaction: Modern Methods and Applications". This Special Issue covered a wide range of topics connected to the theory and application of different computational intelligence techniques to the domain of human–computer interaction, such as automatic speech recognition, speech processing and analysis, virtual reality, emotion-aware applications, digital storytelling, natural language processing, smart cars and devices, and online learning. We hope that this book will be interesting and useful for those working in various areas of artificial intelligence, human–computer interaction, and software engineering as well as for those who are interested in how these domains are connected in real-life situations

    IoT and Sensor Networks in Industry and Society

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    The exponential progress of Information and Communication Technology (ICT) is one of the main elements that fueled the acceleration of the globalization pace. Internet of Things (IoT), Artificial Intelligence (AI) and big data analytics are some of the key players of the digital transformation that is affecting every aspect of human's daily life, from environmental monitoring to healthcare systems, from production processes to social interactions. In less than 20 years, people's everyday life has been revolutionized, and concepts such as Smart Home, Smart Grid and Smart City have become familiar also to non-technical users. The integration of embedded systems, ubiquitous Internet access, and Machine-to-Machine (M2M) communications have paved the way for paradigms such as IoT and Cyber Physical Systems (CPS) to be also introduced in high-requirement environments such as those related to industrial processes, under the forms of Industrial Internet of Things (IIoT or I2oT) and Cyber-Physical Production Systems (CPPS). As a consequence, in 2011 the German High-Tech Strategy 2020 Action Plan for Germany first envisioned the concept of Industry 4.0, which is rapidly reshaping traditional industrial processes. The term refers to the promise to be the fourth industrial revolution. Indeed, the first industrial revolution was triggered by water and steam power. Electricity and assembly lines enabled mass production in the second industrial revolution. In the third industrial revolution, the introduction of control automation and Programmable Logic Controllers (PLCs) gave a boost to factory production. As opposed to the previous revolutions, Industry 4.0 takes advantage of Internet access, M2M communications, and deep learning not only to improve production efficiency but also to enable the so-called mass customization, i.e. the mass production of personalized products by means of modularized product design and flexible processes. Less than five years later, in January 2016, the Japanese 5th Science and Technology Basic Plan took a further step by introducing the concept of Super Smart Society or Society 5.0. According to this vision, in the upcoming future, scientific and technological innovation will guide our society into the next social revolution after the hunter-gatherer, agrarian, industrial, and information eras, which respectively represented the previous social revolutions. Society 5.0 is a human-centered society that fosters the simultaneous achievement of economic, environmental and social objectives, to ensure a high quality of life to all citizens. This information-enabled revolution aims to tackle today’s major challenges such as an ageing population, social inequalities, depopulation and constraints related to energy and the environment. Accordingly, the citizens will be experiencing impressive transformations into every aspect of their daily lives. This book offers an insight into the key technologies that are going to shape the future of industry and society. It is subdivided into five parts: the I Part presents a horizontal view of the main enabling technologies, whereas the II-V Parts offer a vertical perspective on four different environments. The I Part, dedicated to IoT and Sensor Network architectures, encompasses three Chapters. In Chapter 1, Peruzzi and Pozzebon analyse the literature on the subject of energy harvesting solutions for IoT monitoring systems and architectures based on Low-Power Wireless Area Networks (LPWAN). The Chapter does not limit the discussion to Long Range Wise Area Network (LoRaWAN), SigFox and Narrowband-IoT (NB-IoT) communication protocols, but it also includes other relevant solutions such as DASH7 and Long Term Evolution MAchine Type Communication (LTE-M). In Chapter 2, Hussein et al. discuss the development of an Internet of Things message protocol that supports multi-topic messaging. The Chapter further presents the implementation of a platform, which integrates the proposed communication protocol, based on Real Time Operating System. In Chapter 3, Li et al. investigate the heterogeneous task scheduling problem for data-intensive scenarios, to reduce the global task execution time, and consequently reducing data centers' energy consumption. The proposed approach aims to maximize the efficiency by comparing the cost between remote task execution and data migration. The II Part is dedicated to Industry 4.0, and includes two Chapters. In Chapter 4, Grecuccio et al. propose a solution to integrate IoT devices by leveraging a blockchain-enabled gateway based on Ethereum, so that they do not need to rely on centralized intermediaries and third-party services. As it is better explained in the paper, where the performance is evaluated in a food-chain traceability application, this solution is particularly beneficial in Industry 4.0 domains. Chapter 5, by De Fazio et al., addresses the issue of safety in workplaces by presenting a smart garment that integrates several low-power sensors to monitor environmental and biophysical parameters. This enables the detection of dangerous situations, so as to prevent or at least reduce the consequences of workers accidents. The III Part is made of two Chapters based on the topic of Smart Buildings. In Chapter 6, Petroșanu et al. review the literature about recent developments in the smart building sector, related to the use of supervised and unsupervised machine learning models of sensory data. The Chapter poses particular attention on enhanced sensing, energy efficiency, and optimal building management. In Chapter 7, Oh examines how much the education of prosumers about their energy consumption habits affects power consumption reduction and encourages energy conservation, sustainable living, and behavioral change, in residential environments. In this Chapter, energy consumption monitoring is made possible thanks to the use of smart plugs. Smart Transport is the subject of the IV Part, including three Chapters. In Chapter 8, Roveri et al. propose an approach that leverages the small world theory to control swarms of vehicles connected through Vehicle-to-Vehicle (V2V) communication protocols. Indeed, considering a queue dominated by short-range car-following dynamics, the Chapter demonstrates that safety and security are increased by the introduction of a few selected random long-range communications. In Chapter 9, Nitti et al. present a real time system to observe and analyze public transport passengers' mobility by tracking them throughout their journey on public transport vehicles. The system is based on the detection of the active Wi-Fi interfaces, through the analysis of Wi-Fi probe requests. In Chapter 10, Miler et al. discuss the development of a tool for the analysis and comparison of efficiency indicated by the integrated IT systems in the operational activities undertaken by Road Transport Enterprises (RTEs). The authors of this Chapter further provide a holistic evaluation of efficiency of telematics systems in RTE operational management. The book ends with the two Chapters of the V Part on Smart Environmental Monitoring. In Chapter 11, He et al. propose a Sea Surface Temperature Prediction (SSTP) model based on time-series similarity measure, multiple pattern learning and parameter optimization. In this strategy, the optimal parameters are determined by means of an improved Particle Swarm Optimization method. In Chapter 12, Tsipis et al. present a low-cost, WSN-based IoT system that seamlessly embeds a three-layered cloud/fog computing architecture, suitable for facilitating smart agricultural applications, especially those related to wildfire monitoring. We wish to thank all the authors that contributed to this book for their efforts. We express our gratitude to all reviewers for the volunteering support and precious feedback during the review process. We hope that this book provides valuable information and spurs meaningful discussion among researchers, engineers, businesspeople, and other experts about the role of new technologies into industry and society

    Telecommunications Networks

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    This book guides readers through the basics of rapidly emerging networks to more advanced concepts and future expectations of Telecommunications Networks. It identifies and examines the most pressing research issues in Telecommunications and it contains chapters written by leading researchers, academics and industry professionals. Telecommunications Networks - Current Status and Future Trends covers surveys of recent publications that investigate key areas of interest such as: IMS, eTOM, 3G/4G, optimization problems, modeling, simulation, quality of service, etc. This book, that is suitable for both PhD and master students, is organized into six sections: New Generation Networks, Quality of Services, Sensor Networks, Telecommunications, Traffic Engineering and Routing

    Distributed radiofrequency signal processing based on space-division multiplexing fibers

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    [EN] Space-division multiplexing fibers emerged as a promising solution to overcome the imminent capacity crunch of conventional singlemode fiber networks. Despite these fibers were initially conceived as distribution media for long-haul high-capacity digital communications, they can be applied to a wide variety of scenarios including centralized radio access networks for wireless communications, data-center interconnects, Microwave Photonics signal processing and fiber sensing. Particular interest is raised by emerging communications paradigms, such as 5G and The Internet of Things, which require a full integration between the optical fiber and the wireless networks segments. Microwave Photonics, discipline that focuses on the generation, processing, control and distribution of radiofrequency signals by photonics means, is called to play a decisive role. One of the major challenges that Microwave Photonics has to overcome to satisfy next-generation communication demands relates to the reduction of size, weight and power consumption while assuring broadband seamless reconfigurability and stability. There is one revolutionary approach that has however been left untapped in finding innovative ways to address that challenge: exploiting space, the last available degree of freedom for optical multiplexing. In this Thesis, we propose to exploit the inherent parallelism of multicore and few-mode fibers to implement sampled discrete true time delay lines, providing, in a single optical fiber, a compact and efficient approach for both Microwave Photonics signal distribution and processing. For the multicore fiber approach, we study the influence of the refractive index profile of each heterogeneous core on the propagation characteristics as to feature specific group delay and chromatic dispersion values. We designed and fabricated two different heterogeneous trench-assisted 7-core fibers that behave as sampled true time delay lines. While one of them was fabricated by using 7 different preforms to feature a plenary performance, the other one employed a single preform with the aim of minimizing fabrication costs. In the case of few-mode fibers, we propose the implementation of a tunable true time delay line by means of a custom-designed fiber with a set of inscribed long period gratings that act as mode converters to properly tailor the sample group delays. We designed and fabricated a true time delay line on a 4-mode fiber by inscribing 3 long period gratings at specific positions along the fiber link. As a proof-of-concept validation, we experimentally demonstrated different Microwave Photonics signal processing functionalities implemented over both multicore and few-mode fiber approaches. This work opens the way towards the development of distributed signal processing for microwave and millimeter wave signals in a single optical fiber. These true time delay lines can be applied to a wide range of Information and Communication Technology paradigms besides fiber-wireless communications such as broadband satellite communications, distributed sensing, medical imaging, optical coherence tomography and quantum communications.[ES] La multiplexación por división espacial en fibras ópticas surgió como una solución prometedora al inminente colapso en la capacidad de las redes de fibra monomodo convencionales. Aunque estas fibras fueron concebidas inicialmente como medio de distribución en comunicaciones digitales de larga distancia y alta capacidad, pueden emplearse en una amplia variedad de escenarios, incluyendo redes de acceso radio centralizadas para comunicaciones inalámbricas, interconexiones en centros de datos, así como procesado de señal en Fotónica de Microondas y sensado en fibra. Los paradigmas de comunicaciones emergentes despiertan un interés particular, como 5G y el Internet de las Cosas, que requieren una integración total entre el segmento de red de fibra óptica y el inalámbrico. La Fotónica de Microondas, disciplina que se focaliza en la generación, procesado, control y distribución de señales de radiofrecuencia por medio de la fotónica, está destinada a jugar un papel decisivo. Uno de los mayores desafíos que la Fotónica de Microondas debe superar para satisfacer los requisitos de las nuevas generaciones de comunicaciones se basa en la reducción de tamaño, peso y consumo de potencia, mientras se garantiza reconfiguración y estabilidad de banda ancha. Encontramos aquí un enfoque revolucionario capaz de abordar este desafío de una manera innovadora que, sin embargo, no ha sido aprovechado en este contexto: la explotación del espacio, el último grado de libertad para multiplexación óptica. En esta Tesis, proponemos explotar el paralelismo inherente de las fibras ópticas multinúcleo y de pocos modos para implementar líneas de retardo en tiempo real muestreadas que proporcionan, en una sola fibra óptica, una solución compacta y eficiente tanto para distribución como para procesado de señales de Fotónica de Microondas. En el caso de fibras multinúcleo, estudiamos la influencia del perfil de índice de refracción de cada núcleo heterogéneo en las características de propagación para que exhiba unos valores concretos de retardo de grupo y dispersión cromática. Diseñamos y fabricamos dos fibras distintas de 7 núcleos con zanjas que se comportan como líneas de retardo en tiempo real muestreadas. Mientras que una de ellas se fabricó utilizando 7 preformas diferentes para garantizar un funcionamiento completo, la segunda se fabricó utilizando una única preforma con el objetivo de minimizar costes de fabricación. En el caso de fibras de pocos modos, proponemos la implementación de líneas de retardo en tiempo real sintonizables mediante el uso de una fibra específicamente diseñada y la inscripción de un conjunto de redes de difracción de periodo largo que actúan como conversores de modos para ajustar adecuadamente el retardo de grupo de las muestras. Diseñamos y fabricamos una línea de retardo en tiempo real en una fibra de 4 modos mediante la inscripción de 3 redes de difracción de periodo largo en posiciones concretas a lo largo de enlace de fibra. Como validación de prueba de concepto, demostramos experimentalmente diferentes funcionalidades de procesado de señal de Fotónica de Microondas implementadas en fibras multinúcleo y de pocos modos. Este trabajo abre el camino hacia el desarrollo del procesado de señal distribuido para señales de microondas y ondas milimétricas en una única fibra óptica. Además, las líneas de retardo en tiempo real desarrolladas pueden aplicarse a una amplia variedad de paradigmas de Tecnologías de la Información y Comunicaciones más allá de las comunicaciones radio sobre fibra, como es el caso de las comunicaciones de banda ancha por satélite, el sensado distribuido, la imagen médica, la tomografía óptica coherente y las comunicaciones cuánticas.[CA] La multiplexació per divisió espacial en fibres òptiques va sorgir com una solució prometedora a l'imminent col·lapse en la capacitat de les xarxes de fibra monomode convencionals. Encara que estes fibres foren concebudes inicialment com a mitjà de distribució en comunicacions digitals de llarga distància i alta capacitat, poden emprar-se en una àmplia varietat d'escenaris, incloent xarxes d'accés radio centralitzades per a comunicacions sense fils, interconnexions en centres de dades, així com processat de senyal en Fotònica de Microones i sensat en fibra. Els paradigmes de comunicacions emergents desperten un interès particular, com el 5G i la Internet de les Coses, que requereixen una integració total entre els segments de xarxa de fibra òptica i el de sense fils. La Fotònica de Microones, disciplina que es focalitza en la generació, processat, control i distribució de senyals de radiofreqüència per mitjà de la fotònica, està destinada a jugar un paper decisiu. Un dels majors desafiaments que la Fotònica de Microones ha de superar per satisfer els requisits de les noves generacions de comunicacions es basa en la reducció de grandària, pes i consum de potència, mentre es garanteix reconfiguració i estabilitat de banda ampla Trobem ací un enfocament revolucionari capaç d'abordar aquest desafiament d'una manera innovadora que, no obstant això, no ha sigut aprofitat encara en este context: la explotació de l'espai, l'últim grau de llibertat per a multiplexat òptic. En aquesta Tesi, proposem explotar el paral·lelisme inherent de les fibres òptiques multinucli i de pocs modes per a implementar línies de retard en temps real de mostres discretes que proporcionen, en una sola fibra òptica, una solució compacta i eficient tant per a distribució com per a processat de senyals de Fotònica de Microones. En el cas de fibres multinucli, estudiem la influència del perfil d'índex de refracció de cada nucli heterogeni en les característiques de propagació perquè exhibisca uns valors concrets de retard de grup i dispersió cromàtica. Dissenyem i fabriquem dues fibres distintes de 7 nuclis amb rases que es comporten com a línies de retard en temps real mostrejades. Mentre que una d'elles es va fabricar utilitzant 7 preformes diferents per a garantir un funcionament complet, la segona va fabricar-se utilitzant una única preforma amb l'objectiu de minimitzar costos de fabricació. En el cas de fibres de pocs modes, proposem la implementació de línies de retard en temps real sintonitzables mitjançant l'ús d'una fibra específicament dissenyada i la inscripció d'un conjunt de xarxes de difracció de període llarg que actuen com a convertidors de modes per tal d'ajustar adequadament el retard de grup de les mostres. Dissenyem i fabriquem una línia de retard en temps real en una fibra de 4 modes mitjançant la inscripció de 3 xarxes de difracció de període llarg en posicions concretes al llarg de l'enllaç de fibra. Com a validació de proba de concepte, demostrem experimentalment diferents funcionalitats de processat de senyal de Fotònica de Microones implementades en fibres multinucli i de pocs modes. Aquest treball obri el camí cap al desenvolupament del processat de senyal distribuït per a senyals de microones i ones mil·limètriques en una única fibra òptica. A més, aquestes línies de retard en temps real poden aplicar-se a una àmplia varietat de paradigmes de Tecnologies de la Informació i Comunicacions més enllà de les comunicacions radio sobre fibra, com es el cas de les comunicacions de banda ampla per satèl·lit, el sensat distribuït, la imatge mèdica, la tomografia òptica coherent i les comunicacions quàntiques.Agradezco al Ministerio de Economía y Competitividad del Gobierno de España por la financiación recibida mediante la ayuda FPI.García Cortijo, S. (2020). Distributed radiofrequency signal processing based on space-division multiplexing fibers [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/147858TESI

    Context-aware task scheduling in distributed computing systems

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    These days, the popularity of technologies such as machine learning, augmented reality, and big data analytics is growing dramatically. This leads to a higher demand of computational power not only for IT professionals but also for ordinary device users who benefit from new applications. At the same time, the computational performance of end-user devices increases to meet the demands of these resource-hungry applications. As a result, there is a coexistence of a huge demand of computational power on the one side and a large pool of computational resources on the other side. Bringing these two sides together is the idea of computational resource sharing systems which allow applications to forward computationally intensive workload to remote resources. This technique is often used in cloud computing where customers can rent computational power. However, we argue that not only cloud resources can be used as offloading targets. Rather, idle CPU cycles from end-user administered devices at the edge of the network can be spontaneously leveraged as well. Edge devices, however, are not only heterogeneous in their hardware and software capabilities, they also do not provide any guarantees in terms of reliability or performance. Does it mean that either the applications that require further guarantees or the unpredictable resources need to be excluded from such a sharing system? In this thesis, we propose a solution to this problem by introducing the Tasklet system, our approach for a computational resource sharing system. The Tasklet system supports computation offloading to arbitrary types of devices, including stable cloud instances as well as unpredictable end-user owned edge resources. Therefore, the Tasklet system is structured into multiple layers. The lowest layer is a best-effort resource sharing system which provides lightweight task scheduling and execution. Here, best-effort means that in case of a failure, the task execution is dropped and that tasks are allocated to resources randomly. To provide execution guarantees such as a reliable or timely execution, we add a Quality of Computation (QoC) layer on top of the best-effort execution layer. The QoC layer enforces the guarantees for applications by using a context-aware task scheduler which monitors the available resources in the computing environment and performs the matchmaking between resources and tasks based on the current state of the system. As edge resources are controlled by individuals, we consider the fact that these users need to be able to decide with whom they want to share their resources and for which price. Thus, we add a social layer on top of the system that allows users to establish friendship connections which can then be leveraged for social-aware task allocation and accounting of shared computation

    Elastic computation placement in edge-based environments

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    Today, technologies such as machine learning, virtual reality, and the Internet of Things are integrated in end-user applications more frequently. These technologies demand high computational capabilities. Especially mobile devices have limited resources in terms of execution performance and battery life. The offloading paradigm provides a solution to this problem and transfers computationally intensive parts of applications to more powerful resources, such as servers or cloud infrastructure. Recently, a new computation paradigm arose which exploits the huge amount of end-user devices in the modern computing landscape - called edge computing. These devices encompass smartphones, tablets, microcontrollers, and PCs. In edge computing, devices cooperate with each other while avoiding cloud infrastructure. Due to the proximity among the participating devices, the communication latencies for offloading are reduced. However, edge computing brings new challenges in form of device fluctuation, unreliability, and heterogeneity, which negatively affect the resource elasticity. As a solution, this thesis proposes a computation placement framework that provides an abstraction for computation and resource elasticity in edge-based environments. The design is middleware-based, encompasses heterogeneous platforms, and supports easy integration of existing applications. It is composed of two parts: the Tasklet system and the edge support layer. The Tasklet system is a flexible framework for computation placement on heterogeneous resources. It introduces closed units of computation that can be tailored to generic applications. The edge support layer handles the characteristics of edge resources. It copes with fluctuation and unreliability by applying reactive and proactive task migration. Furthermore, the performance heterogeneity and the consequent bottlenecks are handled by two edge-specific task partitioning approaches. As a proof of concept, the thesis presents a fully-fledged prototype of the design, which is evaluated comprehensively in a real-world testbed. The evaluation shows that the design is able to substantially improve the resource elasticity in edge-based environments
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