SPAD: a distributed middleware architecture for QoS enhanced alternate path discovery

In the next generation Internet, the network will evolve from a plain communication medium into one that provides endless services to the users. These services will be composed of multiple cooperative distributed application elements. We name these services overlay applications. The cooperative application elements within an overlay application will build a dynamic communication mesh, namely an overlay association. The Quality of Service (QoS) perceived by the users of an overlay application greatly depends on the QoS experienced on the communication paths of the corresponding overlay association. In this paper, we present SPAD (Super-Peer Alternate path Discovery), a distributed middleware architecture that aims at providing enhanced QoS between end-points within an overlay association. To achieve this goal, SPAD provides a complete scheme to discover and utilize composite alternate end-to end paths with better QoS than the path given by the default IP routing mechanisms

Propagation measurements and estimation of channel propagation models in urban environment

Wireless communication is a telecommunication technology, which enables wireless transmission between the portable devices to provide wireless access in all types of environments. In this research, the measurements and various empirical models are analysed and compared in order to find out a suitable propagation model to provide guidelines for cell planning of wireless communication systems. The measured data was taken in urban region with low vegetation and some trees at 900 MHz frequency band. Path loss models are useful planning tools, which permit the designers of cellular communication to obtain optimal levels for the base station deployment and meeting the expected service level requirements. Outcomes show that these empirical models tend to overestimate the propagation loss. As one of the key outputs, it was observed that the calculations of Weissberger model fit with the measured data in urban environment

Solutions for New Terrestrial Broadcasting Systems Offering Simultaneously Stationary and Mobile Services

221 p.[EN]Since the first broadcasted TV signal was transmitted in the early decades of the past century, the television broadcasting industry has experienced a series of dramatic changes. Most recently, following the evolution from analogue to digital systems, the digital dividend has become one of the main concerns of the broadcasting industry. In fact, there are many international spectrum authorities reclaiming part of the broadcasting spectrum to satisfy the growing demand of other services, such as broadband wireless services, arguing that the TV services are not very spectrum-efficient. Apart from that, it must be taken into account that, even if up to now the mobile broadcasting has not been considered a major requirement, this will probably change in the near future. In fact, it is expected that the global mobile data traffic will increase 11-fold between 2014 and 2018, and what is more, over two thirds of the data traffic will be video stream by the end of that period. Therefore, the capability to receive HD services anywhere with a mobile device is going to be a mandatory requirement for any new generation broadcasting system. The main objective of this work is to present several technical solutions that answer to these challenges. In particular, the main questions to be solved are the spectrum efficiency issue and the increasing user expectations of receiving high quality mobile services. In other words, the main objective is to provide technical solutions for an efficient and flexible usage of the terrestrial broadcasting spectrum for both stationary and mobile services. The first contributions of this scientific work are closely related to the study of the mobile broadcast reception. Firstly, a comprehensive mathematical analysis of the OFDM signal behaviour over time-varying channels is presented. In order to maximize the channel capacity in mobile environments, channel estimation and equalization are studied in depth. First, the most implemented equalization solutions in time-varying scenarios are analyzed, and then, based on these existing techniques, a new equalization algorithm is proposed for enhancing the receivers’ performance. An alternative solution for improving the efficiency under mobile channel conditions is treating the Inter Carrier Interference as another noise source. Specifically, after analyzing the ICI impact and the existing solutions for reducing the ICI penalty, a new approach based on the robustness of FEC codes is presented. This new approach employs one dimensional algorithms at the receiver and entrusts the ICI removing task to the robust forward error correction codes. Finally, another major contribution of this work is the presentation of the Layer Division Multiplexing (LDM) as a spectrum-efficient and flexible solution for offering stationary and mobile services simultaneously. The comprehensive theoretical study developed here verifies the improved spectrum efficiency, whereas the included practical validation confirms the feasibility of the system and presents it as a very promising multiplexing technique, which will surely be a strong candidate for the next generation broadcasting services.[ES]Desde el comienzo de la transmisión de las primeras señales de televisión a principios del siglo pasado, la radiodifusión digital ha evolucionado gracias a una serie de cambios relevantes. Recientemente, como consecuencia directa de la digitalización del servicio, el dividendo digital se ha convertido en uno de los caballos de batalla de la industria de la radiodifusión. De hecho, no son pocos los consorcios internacionales que abogan por asignar parte del espectro de radiodifusión a otros servicios como, por ejemplo, la telefonía móvil, argumentado la poca eficiencia espectral de la tecnología de radiodifusión actual. Asimismo, se debe tener en cuenta que a pesar de que los servicios móviles no se han considerado fundamentales en el pasado, esta tendencia probablemente variará en el futuro cercano. De hecho, se espera que el tráfico derivado de servicios móviles se multiplique por once entre los años 2014 y 2018; y lo que es más importante, se pronostica que dos tercios del tráfico móvil sea video streaming para finales de ese periodo. Por lo tanto, la posibilidad de ofrecer servicios de alta definición en dispositivos móviles es un requisito fundamental para los sistemas de radiodifusión de nueva generación. El principal objetivo de este trabajo es presentar soluciones técnicas que den respuesta a los retos planteados anteriormente. En particular, las principales cuestiones a resolver son la ineficiencia espectral y el incremento de usuarios que demandan mayor calidad en los contenidos para dispositivos móviles. En pocas palabras, el principal objetivo de este trabajo se basa en ofrecer una solución más eficiente y flexible para la transmisión simultánea de servicios fijos y móviles. La primera contribución relevante de este trabajo está relacionada con la recepción de la señal de televisión en movimiento. En primer lugar, se presenta un completo análisis matemático del comportamiento de la señal OFDM en canales variantes con el tiempo. A continuación, con la intención de maximizar la capacidad del canal, se estudian en profundidad los algoritmos de estimación y ecualización. Posteriormente, se analizan los algoritmos de ecualización más implementados, y por último, basándose en estas técnicas, se propone un nuevo algoritmo de ecualización para aumentar el rendimiento de los receptores en tales condiciones. Del mismo modo, se plantea un nuevo enfoque para mejorar la eficiencia de los servicios móviles basado en tratar la interferencia entre portadoras como una fuente de ruido. Concretamente, tras analizar el impacto del ICI en los receptores actuales, se sugiere delegar el trabajo de corrección de dichas distorsiones en códigos FEC muy robustos. Finalmente, la última contribución importante de este trabajo es la presentación de la tecnología LDM como una manera más eficiente y flexible para la transmisión simultánea de servicios fijos y móviles. El análisis teórico presentado confirma el incremento en la eficiencia espectral, mientras que el estudio práctico valida la posible implementación del sistema y presenta la tecnología LDM c

Internet of Things-based Traffic Management System for Maseru, Lesotho.

Published ThesisThe number of vehicles in Maseru has been steadily increasing, leading to heightened intensity of congestion and traffic occurrences. This is further exacerbated by ineffective solutions that are currently in place as well as the absence of tools that facilitate dispersal of information to motorists. Traffic lights have been put in place to manage flow of traffic but are becoming increasingly inefficient due to their design. The preset timing cycles between green, amber and red disregarding prevailing conditions leads, inter alia, to increased wait times, use of additional fuel and air pollution. In addition, lack of equipment that is able to provide motorists with information about prevailing road conditions further increases the possibility of one being stuck in traffic. To make traffic management more efficient at signaled junctions, the implementation of the Internet of Things (IoT) paradigm is used to create intelligent traffic management systems such as Wireless Sensor Networks (WSN) and fuzzy algorithms to intelligently decide the phases of traffic lights. Road density and vehicles’ speeds are collected from the road infrastructure using cameras and are passed to a fuzzy algorithm to determine how congested a road is. Dependent on these parameters, the algorithm will also determine which roads should be given highest priority while maintaining a degree of fairness, thus optimizing traffic flow. In addition, the ubiquitous provision of road condition information to motorists in various formats such as text and audio is also used. This feature allows for the acquisition of the latest road status, thus making it possible to find alternative routes. The unique feature in this project is the ability to collect road parameters from the road infrastructure itself, using WSN as well as crowd source data from road users using mobile devices. A study conducted in this research revealed a relationship between the number of cars on a road and concentration of Carbon Dioxide (CO2); the results showed that as the number of cars increases, so does the measure of CO2. Questionnaire-based surveys showed that Maseru citizens have noted an increase in congestion which they attributed to the increase in number of vehicles on the road that is not met by the increase or improvement in road infrastructure. The respondents in this survey also noted limited mechanisms that provide them with road conditions and highlighted that such tools may alleviate congestion. The performance of intelligent traffic lights was conducted via simulations compared with fixed cycle traffic lights. From the simulations it was observed that IoT- based traffic management systems reduced the wait times of vehicles at signaled junctions which would also result in reduction of the pollutant CO2. It is envisaged that the future implementation will include the ability to manage a network of junctions and ability to predict abnormal traffic flows

Sensitivity analysis and related analysis: A survey of statistical techniques

This paper reviews the state of the art in five related types of analysis, namely (i) sensitivity or what-if analysis, (ii) uncertainty or risk analysis, (iii) screening, (iv) validation, and (v) optimization. The main question is: when should which type of analysis be applied; which statistical techniques may then be used? This paper distinguishes the following five stages in the analysis of a simulation model. 1) Validation: the availability of data on the real system determines which type of statistical technique to use for validation. 2) Screening: in the simulation's pilot phase the really important inputs can be identified through a novel technique, called sequential bifurcation, which uses aggregation and sequential experimentation. 3) Sensitivity analysis: the really important inputs should be This approach with its five stages implies that sensitivity analysis should precede uncertainty analysis. This paper briefly discusses several case studies for each phase.Experimental Design;Statistical Methods;Regression Analysis;Risk Analysis;Least Squares;Sensitivity Analysis;Optimization;Perturbation;statistics

Quality of Service and Associated Communication Infrastructure for Electric Vehicles †

Transportation electrification is pivotal for achieving energy security and emission reduction goals. Electric vehicles (EVs) are at the forefront of this transition, driving the development of new EV technologies and infrastructure. As this trend gains momentum, it becomes essential to enhance the quality of service (QoS) of EVs to encourage their widespread adoption. This paper has been structured with two primary aims to effectively address the above timely technological needs. Firstly, it comprehensively reviews the various QoS factors that influence EVs’ performance and the user experience. Delving into these factors provides valuable insights into how the QoS can be improved, thereby fostering the increased use of EVs on our roads. In addition to the QoS, this paper also explores recent advancements in communication technologies vital for facilitating in-formation exchanges between EVs and charging stations. Efficient communication systems are crucial for optimizing EV operations and enhancing user experiences. This paper presents expert-level technical details in an easily understandable manner, making it a valuable resource for researchers dedicated to improving the QoS of EV communication systems, who are tirelessly working towards a cleaner, more efficient future in transportation. It consolidates the current knowledge in the field and presents the latest discoveries and developments, offering practical insights for enhancing the QoS in electric transportation. A QoS parameter reference map, a detailed classification of QoS parameters, and a classification of EV communication technology references are some of the key contributions of this review paper. In doing so, this paper contributes to the broader objectives of promoting transportation electrification, enhancing energy security, and reducing emissions

Estimation of Travel Time using Temporal and Spatial Relationships in Sparse Data

Travel time is a basic measure upon which e.g. traveller information systems, traffic management systems, public transportation planning and other intelligent transport systems are developed. Collecting travel time information in a large and dynamic road network is essential to managing the transportation systems strategically and efficiently. This is a challenging and expensive task that requires costly travel time measurements. Estimation techniques are employed to utilise data collected for the major roads and traffic network structure to approximate travel times for minor links. Although many methodologies have been proposed, they have not yet adequately solved many challenges associated with travel time, in particular, travel time estimation for all links in a large and dynamic urban traffic network. Typically focus is placed on major roads such as motorways and main city arteries but there is an increasing need to know accurate travel times for minor urban roads. Such information is crucial for tackling air quality problems, accommodate a growing number of cars and provide accurate information for routing, e.g. self-driving vehicles. This study aims to address the aforementioned challenges by introducing a methodology able to estimate travel times in near-real-time by using historical sparse travel time data. To this end, an investigation of temporal and spatial dependencies between travel time of traffic links in the datasets is carefully conducted. Two novel methodologies are proposed, Neighbouring Link Inference method (NLIM) and Similar Model Searching method (SMS). The NLIM learns the temporal and spatial relationship between the travel time of adjacent links and uses the relation to estimate travel time of the targeted link. For this purpose, several machine learning techniques including support vector machine regression, neural network and multi-linear regression are employed. Meanwhile, SMS looks for similar NLIM models from which to utilise data in order to improve the performance of a selected NLIM model. NLIM and SMS incorporates an additional novel application for travel time outlier detection and removal. By adapting a multivariate Gaussian mixture model, an improvement in travel time estimation is achieved. Both introduced methods are evaluated on four distinct datasets and compared against benchmark techniques adopted from literature. They efficiently perform the task of travel time estimation in near-real-time of a target link using models learnt from adjacent traffic links. The training data from similar NLIM models provide more information for NLIM to learn the temporal and spatial relationship between the travel time of links to support the high variability of urban travel time and high data sparsity.Ministry of Education and Training of Vietna

Learning Opportunities and Challenges of Sensor-enabled Intelligent Tutoring Systems on Mobile Platforms: Benchmarking the Reliability of Mobile Sensors to Track Human Physiological Signals and Behaviors to Enhance Tablet-Based Intelligent Tutoring Systems

Desktop-based intelligent tutoring systems have existed for many decades, but the advancement of mobile computing technologies has sparked interest in developing mobile intelligent tutoring systems (mITS). Personalized mITS are applicable to not only stand-alone and client-server systems but also cloud systems possibly leveraging big data. Device-based sensors enable even greater personalization through capture of physiological signals during periods of student study. However, personalizing mITS to individual students faces challenges. The Achilles heel of personalization is the feasibility and reliability of these sensors to accurately capture physiological signals and behavior measures. This research reviews feasibility and benchmarks reliability of basic mobile platform sensors in various student postures. The research software and methodology are generalizable to a range of platforms and sensors. Incorporating the tile-based puzzle game 2048 as a substitute for a knowledge domain also enables a broad spectrum of test populations. Baseline sensors include the on-board camera to detect eyes/faces and the Bluetooth Empatica E4 wristband to capture heart rate, electrodermal activity (EDA), and skin temperature. The test population involved 100 collegiate students randomly assigned to one of three different ergonomic positions in a classroom: sitting at a table, standing at a counter, or reclining on a sofa. Well received by the students, EDA proved to be more reliable than heart rate or face detection in the three different ergonomic positions. Additional insights are provided on advancing learning personalization through future sensor feasibility and reliability studies