Journal of Telecommunications and Information Technology, 2022, nr 3

kwartalni

Design of static intercell interference coordination schemes for realistic lte-based cellular networks

Today, 3.5 and 4G systems including Long Term Evolution (LTE) and LTE-Advanced (LTE-A) support packet-based services and provide mobile broadband access for bandwidth-hungry applications. In this context of fast evolution, new and challenging technical issues must be e ectively addressed. The nal target is to achieve a signi cant step forward toward the improvement of the Quality of Experience (QoE). To that end, interference management has been recognized by the industry as a key enabler for cellular technologies based on OFDMA. Indeed, with a low frequency reuse factor, intercell interference (ICI) becomes a major concern since the Quality of Service (QoS) is not uniformly delivered across the network, it remarkably depends on user position. Hence, cell edge performance is an important issue in LTE and LTE-A. Intercell Interference Coordination (ICIC) encompasses strategies whose goal is to keep ICI at cell edges as low as possible. This alleviates the aforementioned situation. For this reason, the novelties presented in this Ph.D. thesis include not only developments of static ICIC mechanisms for data and control channels, but also e orts towards further improvements of the energy e ciency perspective. Based on a comprehensive review of the state of the art, a set of research opportunities were identi ed. To be precise, the need for exible performance evaluation methods and optimization frameworks for static ICIC strategies. These mechanisms are grouped in two families: the schemes that de ne constraints on the frequency domain and the ones that propose adjustments on the power levels. Thus, Soft- and Fractional Frequency Reuse (SFR and FFR, respectively) are identi ed as the base of the vast majority of static ICIC proposals. Consequently, during the rst part of this Ph.D. thesis, interesting insights into the operation of SFR and FFR were identi ed beyond well-known facts. These studies allow for the development of a novel statistical framework to evaluate the performance of these schemes in realistic deployments. As a result of the analysis, the poor performance of classic con gurations of SFR and FFR in real-world contexts is shown, and hence, the need for optimization is established. In addition, the importance of the interworking between static ICIC schemes and other network functionalities such as CSI feedback has also been identi ed. Therefore, novel CSI feedback schemes, suitable to operate in conjunction with SFR and FFR, have been developed. These mechanisms exploit the resource allocation pattern of these static ICIC techniques in order to improve the accuracy of the CSI feedback process. The second part is focused on the optimization of SFR and FFR. The use of multiobjective techniques is investigated as a tool to achieve e ective network-speci c optimization. The approach o ers interesting advantages. On the one hand, it allows for simultaneous optimization of several con icting criteria. On the other hand, the multiobjective nature results in outputs composed of several high quality (Pareto e cient) network con gurations, all of them featuring a near-optimal tradeo between the performance criteria. Multiobjective evolutionary algorithms allow employing complex mathematical structures without the need for relaxation, thus capturing accurately the system behavior in terms of ICI. The multiobjective optimization formulation of the problem aims at achieving e ective adjustment of the operational parameters of SFR and FFR both at cell level and network-wide. Moreover, the research was successfully extended to the control channels, both the PDCCH and ePDCCH. Finally, in an e ort to further improve the network energy e ciency (an aspect always considered throughout the thesis), the framework of Cell Switch O (CSO), having close connections with ICIC, is also introduced. By means of the proposed method, signi cant improvements with respect to traditional approaches, baseline con gurations, and previous proposals can be achieved. The gains are obtained in terms of energy consumption, network capacity, and cell edge performance.Actualmente los sistemas 3.5 y 4G tales como Long Term Evolution (LTE) y LTE-Advanced (LTE-A) soportan servicios basados en paquetes y proporcionan acceso de banda ancha m ovil para aplicaciones que requieren elevadas tasas de transmisi on. En este contexto de r apida evoluci on, aparecen nuevos retos t ecnicos que deben ser resueltos e cientemente. El objetivo ultimo es conseguir un salto cualitativo importante en la experiencia de usuario (QoE). Con tal n, un factor clave que ha sido reconocido en las redes celulares basadas en Orthogonal Frequency- Division Multiple Access (OFDMA) es la gesti on de interferencias. De hecho, la utilizaci on de un factor de reuso bajo permite una elevada e ciencia espectral pero a costa de una distribuci on de la calidad de servicio (QoS) que no es uniforme en la red, depende de la posici on del usuario. Por lo tanto, el rendimiento en los l mites de la celda se ve muy penalizado y es un problema importante a resolver en LTE y LTE-A. La coordinaci on de interferencias entre celdas (ICIC, del ingl es Intercell Interfe- rence Coordination) engloba las estrategias cuyo objetivo es mantener la interferencia intercelular (ICI) lo m as baja posible en los bordes de celda. Esto permite aliviar la situaci on antes mencionada. La contribuci on presentada en esta tesis doctoral incluye el dise~no de nuevos mecanismos de ICIC est atica para los canales de datos y control, as como tambi en mejoras desde el punto de vista de e ciencia energ etica. A partir de una revisi on completa del estado del arte, se identi caron una serie de retos abiertos que requer an esfuerzos de investigaci on. En concreto, la necesidad de m etodos de evaluaci on exibles y marcos de optimizaci on de las estrategias de ICIC est aticas. Estos mecanismos se agrupan en dos familias: los esquemas que de nen restricciones sobre el dominio de la frecuencia y los que proponen ajustes en los niveles de potencia. Es decir, la base de la gran mayor a de propuestas ICIC est aticas son la reutilizaci on de frecuencias de tipo soft y fraccional (SFR y FFR, respectivamente). De este modo, durante la primera parte de esta tesis doctoral, se han estudiado los aspectos m as importantes del funcionamiento de SFR y FFR, haciendo especial enfasis en las conclusiones que van m as all a de las bien conocidas. Ello ha permitido introducir un nuevo marco estad stico para evaluar el funcionamiento de estos sistemas en condiciones de despliegue reales. Como resultado de estos an alisis, se muestra el pobre desempe~no de SFR y FFR en despliegues reales cuando funcionan con sus con guraciones cl asicas y se establece la necesidad de optimizaci on. Tambi en se pone de mani esto la importancia del funcionamiento conjunto entre esquemas ICIC est aticos y otras funcionalidades de la red radio, tales como la informaci on que env an los usuarios sobre el estado de su canal downlink (feedback del CSI, del ingl es Channel State Information). De este modo, se han propuesto diferentes esquemas de feedback apropiados para trabajar conjuntamente con SFR y FFR. Estos mecanismos explotan el patr on de asignaci on de recursos que se utiliza en ICIC est atico para mejorar la precisi on del proceso. La segunda parte se centra en la optimizaci on de SFR y FFR. Se ha investigado el uso de t ecnicas multiobjetivo como herramienta para lograr una optimizaci on e caz, que es espec ca para cada red. El enfoque ofrece ventajas interesantes, por un lado, se permite la optimizaci on simult anea de varios criterios contradictorios. Por otro lado, la naturaleza multiobjetivo implica obtener como resultado con guraciones de red de elevada calidad (Pareto e cientes), todas ellas con un equilibrio casi- optimo entre las diferentes m etricas de rendimiento. Los algoritmos evolucionarios multiobjetivo permiten la utilizaci on de estructuras matem aticas complejas sin necesidad de relajar el problema, de este modo capturan adecuadamente su comportamiento en t erminos de ICI. La formulaci on multiobjetivo consigue un ajuste efectivo de los par ametros operacionales de SFR y FFR, tanto a nivel de celda como a nivel de red. Adem as, la investigaci on se extiende con resultados satisfactorios a los canales de control, PDCCH y ePDCCH. Finalmente, en un esfuerzo por mejorar la e ciencia energ etica de la red (un aspecto siempre considerado a lo largo de la tesis), se introduce en el an alisis global el apagado inteligente de celdas, estrategia con estrechos v nculos con ICIC. A trav es del m etodo propuesto, se obtienen mejoras signi cativas con respecto a los enfoques tradicionales y propuestas previas. Las ganancias se obtienen en t erminos de consumo energ etico, capacidad de la red, y rendimiento en el l mite de las celdas.Actualment els sistemes 3.5 i 4G tals com Long Term Evolution (LTE) i LTE- Advanced (LTE-A) suporten serveis basats en paquets i proporcionen acc es de banda ampla m obil per a aplicacions que requereixen elevades taxes de transmissi o. En aquest context de r apida evoluci o, apareixen nous reptes t ecnics que han de ser resolts e cientment. L'objectiu ultim es aconseguir un salt qualitatiu important en l'experi encia d'usuari (QoE). Amb tal , un factor clau que ha estat reconegut a les xarxes cel lulars basades en Orthogonal Frequency-Division Multiple Access (OFDMA) es la gesti o d'interfer encies. De fet, la utilizaci o d'un factor de re us baix permet una elevada e ci encia espectral per o a costa d'una distribuci o de la qualitat de servei (QoS) que no es uniforme a la xarxa, dep en de la posici o de l'usuari. Per tant, el rendiment en els l mits de la cel la es veu molt penalitzat i es un problema important a resoldre en LTE i LTE-A. La coordinaci o d'interfer encies entre cel les (ICIC, de l'angl es Intercell Interfe- rence Coordination) engloba les estrat egies que tenen com a objectiu mantenir la interfer encia intercel lular (ICI) el m es baixa possible en les vores de la cel la. Aix o permet alleujar la situaci o abans esmentada. La contribuci o presentada en aquesta tesi doctoral inclou el disseny de nous mecanismes de ICIC est atica per als canals de dades i control, aix com tamb e millores des del punt de vista d'e ci encia energ etica. A partir d'una revisi o completa de l'estat de l'art, es van identi car una s erie de reptes oberts que requerien esfor cos de recerca. En concret, la necessitat de m etodes d'avaluaci o exibles i marcs d'optimitzaci o de les estrat egies de ICIC est atiques. Aquests mecanismes s'agrupen en dues fam lies: els esquemes que de neixen restriccions sobre el domini de la freq u encia i els que proposen ajustos en els nivells de pot encia. Es a dir, la base de la gran majoria de propostes ICIC est atiques s on la reutilitzaci o de freq u encies de tipus soft i fraccional (SFR i FFR, respectivament). D'aquesta manera, durant la primera part d'aquesta tesi doctoral, s'han estudiat els aspectes m es importants del funcionament de SFR i FFR, fent especial emfasi en les conclusions que van m es enll a de les ben conegudes. Aix o ha perm es introduir un nou marc estad stic per avaluar el funcionament d'aquests sistemes en condicions de desplegament reals. Com a resultat d'aquestes an alisis, es mostra el pobre acompliment de SFR i FFR en desplegaments reals quan funcionen amb les seves con guracions cl assiques i s'estableix la necessitat d'optimitzaci o. Tamb e es posa de manifest la import ancia del funcionament conjunt entre esquemes ICIC est atics i altres funcionalitats de la xarxa radio, tals com la informaci o que envien els usuaris sobre l'estat del seu canal downlink (feedback del CSI, de l'angl es Channel State Information). D'aquesta manera, s'han proposat diferents esquemes de feedback apropiats per treballar conjuntament amb SFR i FFR. Aquests mecanismes exploten el patr o d'assignaci o de recursos que s'utilitza en ICIC est atic per millorar la precisi o del proc es. La segona part se centra en l'optimitzaci o de SFR i FFR. S'ha investigat l' us de t ecniques multiobjectiu com a eina per aconseguir una optimitzaci o e ca c, que es espec ca per a cada xarxa. L'enfocament ofereix avantatges interessants, d'una banda, es permet l'optimitzaci o simult ania de diversos criteris contradictoris. D'altra banda, la naturalesa multiobjectiu implica obtenir com resultat con guracions de xarxa d'elevada qualitat (Pareto e cients), totes elles amb un equilibri gaireb e optim entre les diferents m etriques de rendiment. Els algorismes evolucionaris multiobjectiu permeten la utilitzaci o d'estructures matem atiques complexes sense necessitat de relaxar el problema, d'aquesta manera capturen adequadament el seu comportament en termes de ICI. La formulaci o multiobjectiu aconsegueix un ajust efectiu dels par ametres operacionals de SFR i FFR, tant a nivell de cel la com a nivell de xarxa. A m es, la recerca s'est en amb resultats satisfactoris als canals de control, PDCCH i ePDCCH. Finalment, en un esfor c per millorar l'e ci encia energ etica de la xarxa (un aspecte sempre considerat al llarg de la tesi), s'introdueix en l'an alisi global l'apagat intel ligent de cel les, estrat egia amb estrets vincles amb ICIC. Mitjan cant el m etode proposat, s'obtenen millores signi catives pel que fa als enfocaments tradicionals i propostes pr evies. Els guanys s'obtenen en termes de consum energ etic, capacitat de la xarxa, i rendiment en el l mit de les cel les

Computational Optimizations for Machine Learning

The present book contains the 10 articles finally accepted for publication in the Special Issue “Computational Optimizations for Machine Learning” of the MDPI journal Mathematics, which cover a wide range of topics connected to the theory and applications of machine learning, neural networks and artificial intelligence. These topics include, among others, various types of machine learning classes, such as supervised, unsupervised and reinforcement learning, deep neural networks, convolutional neural networks, GANs, decision trees, linear regression, SVM, K-means clustering, Q-learning, temporal difference, deep adversarial networks and more. It is hoped that the book will be interesting and useful to those developing mathematical algorithms and applications in the domain of artificial intelligence and machine learning as well as for those having the appropriate mathematical background and willing to become familiar with recent advances of machine learning computational optimization mathematics, which has nowadays permeated into almost all sectors of human life and activity

IoT and Sensor Networks in Industry and Society

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

Text Similarity Between Concepts Extracted from Source Code and Documentation

Context: Constant evolution in software systems often results in its documentation losing sync with the content of the source code. The traceability research field has often helped in the past with the aim to recover links between code and documentation, when the two fell out of sync. Objective: The aim of this paper is to compare the concepts contained within the source code of a system with those extracted from its documentation, in order to detect how similar these two sets are. If vastly different, the difference between the two sets might indicate a considerable ageing of the documentation, and a need to update it. Methods: In this paper we reduce the source code of 50 software systems to a set of key terms, each containing the concepts of one of the systems sampled. At the same time, we reduce the documentation of each system to another set of key terms. We then use four different approaches for set comparison to detect how the sets are similar. Results: Using the well known Jaccard index as the benchmark for the comparisons, we have discovered that the cosine distance has excellent comparative powers, and depending on the pre-training of the machine learning model. In particular, the SpaCy and the FastText embeddings offer up to 80% and 90% similarity scores. Conclusion: For most of the sampled systems, the source code and the documentation tend to contain very similar concepts. Given the accuracy for one pre-trained model (e.g., FastText), it becomes also evident that a few systems show a measurable drift between the concepts contained in the documentation and in the source code.</p

Calibración de un algoritmo de detección de anomalías marítimas basado en la fusión de datos satelitales

La fusión de diferentes fuentes de datos aporta una ayuda significativa en el proceso de toma de decisiones. El presente artículo describe el desarrollo de una plataforma que permite detectar anomalías marítimas por medio de la fusión de datos del Sistema de Información Automática (AIS) para seguimiento de buques y de imágenes satelitales de Radares de Apertura Sintética (SAR). Estas anomalías son presentadas al operador como un conjunto de detecciones que requieren ser monitoreadas para descubrir su naturaleza. El proceso de detección se lleva adelante primero identificando objetos dentro de las imágenes SAR a través de la aplicación de algoritmos CFAR, y luego correlacionando los objetos detectados con los datos reportados mediante el sistema AIS. En este trabajo reportamos las pruebas realizadas con diferentes configuraciones de los parámetros para los algoritmos de detección y asociación, analizamos la respuesta de la plataforma y reportamos la combinación de parámetros que reporta mejores resultados para las imágenes utilizadas. Este es un primer paso en nuestro objetivo futuro de desarrollar un sistema que ajuste los parámetros en forma dinámica dependiendo de las imágenes disponibles.XVI Workshop Computación Gráfica, Imágenes y Visualización (WCGIV)Red de Universidades con Carreras en Informática (RedUNCI

XXIII Congreso Argentino de Ciencias de la Computación - CACIC 2017 : Libro de actas

Trabajos presentados en el XXIII Congreso Argentino de Ciencias de la Computación (CACIC), celebrado en la ciudad de La Plata los días 9 al 13 de octubre de 2017, organizado por la Red de Universidades con Carreras en Informática (RedUNCI) y la Facultad de Informática de la Universidad Nacional de La Plata (UNLP).Red de Universidades con Carreras en Informática (RedUNCI