Modelling and Analysis of Resource Management Schemes in Wireless Networks. Analytical Models and Performance Evaluation of Handoff Schemes and Resource Re-Allocation in Homogeneous and Heterogeneous Wireless Cellular Networks.

Over recent years, wireless communication systems have been experiencing a dramatic and continuous growth in the number of subscribers, thus placing extra demands on system capacity. At the same time, keeping Quality of Service (QoS) at an acceptable level is a critical concern and a challenge to the wireless network designer. In this sense, performance analysis must be the first step in designing or improving a network. Thus, powerful mathematical tools for analysing most of the performance metrics in the network are required. A good modelling and analysis of the wireless cellular networks will lead to a high level of QoS. In this thesis, different analytical models of various handoff schemes and resource re-allocation in homogeneous and heterogeneous wireless cellular networks are developed and investigated. The sustained increase in users and the request for advanced services are some of the key motivations for considering the designing of Hierarchical Cellular Networks (HCN). In this type of system, calls can be blocked in a microcell flow over to an overlay macrocell. Microcells in the HCN can be replaced by WLANs as this can provide high bandwidth and its users have limited mobility features. Efficient sharing of resources between wireless cellular networks and WLANs will improve the capacity as well as QoS metrics. This thesis first presents an analytical model for priority handoff mechanisms, where new calls and handoff calls are captured by two different traffic arrival processes, respectively. Using this analytical model, the optimised number of channels assigned to II handover calls, with the aim of minimising the drop probability under given network scenarios, has been investigated. Also, an analytical model of a network containing two cells has been developed to measure the different performance parameters for each of the cells in the network, as well as altogether as one network system. Secondly, a new solution is proposed to manage the bandwidth and re-allocate it in a proper way to maintain the QoS for all types of calls. Thirdly, performance models for microcells and macrocells in hierarchical cellular networks have been developed by using a combination of different handoff schemes. Finally, the microcell in HCN is replaced by WLANs and a prioritised vertical handoff scheme in an integrated UMTS/WLAN network has been developed. Simulation experiments have been conducted to validate the accuracy of these analytical models. The models have then been used to investigate the performance of the networks under different scenarios

Resource Allocation for Cellular/WLAN Integrated Networks

The next-generation wireless communications have been envisioned to be supported by heterogeneous networks using various wireless access technologies. The popular cellular networks and wireless local area networks (WLANs) present perfectly complementary characteristics in terms of service capacity, mobility support, and quality-of-service (QoS) provisioning. The cellular/WLAN interworking is thus an effective way to promote the evolution of wireless networks. As an essential aspect of the interworking, resource allocation is vital for efficient utilization of the overall resources. Specially, multi-service provisioning can be enhanced with cellular/WLAN interworking by taking advantage of the complementary network strength and an overlay structure. Call assignment/reassignment strategies and admission control policies are effective resource allocation mechanisms for the cellular/WLAN integrated network. Initially, the incoming calls are distributed to the overlay cell or WLAN according to call assignment strategies, which are enhanced with admission control policies in the target network. Further, call reassignment can be enabled to dynamically transfer the traffic load between the overlay cell and WLAN via vertical handoff. By these means, the multi-service traffic load can be properly shared between the interworked systems. In this thesis, we investigate the load sharing problem for this heterogeneous wireless overlay network. Three load sharing schemes with different call assignment/reassignment strategies and admission control policies are proposed and analyzed. Effective analytical models are developed to evaluate the QoS performance and determine the call admission and assignment parameters. First, an admission control scheme with service-differentiated call assignment is studied to gain insights on the effects of load sharing on interworking effectiveness. Then, the admission scheme is extended by using randomized call assignment to enable distributed implementation. Also, we analyze the impact of user mobility and data traffic variability. Further, an enhanced call assignment strategy is developed to exploit the heavy-tailedness of data call size. Last, the study is extended to a multi-service scenario. The overall resource utilization and QoS satisfaction are improved substantially by taking into account the multi-service traffic characteristics, such as the delay-sensitivity of voice traffic, elasticity and heavy-tailedness of data traffic, and rate-adaptiveness of video streaming traffic

Comunicações veiculares híbridas

Vehicle Communications is a promising research field, with a great potential for the development of new applications capable of improving road safety, traffic efficiency, as well as passenger comfort and infotainment. Vehicle communication technologies can be short-range, such as ETSI ITS-G5 or the 5G PC5 sidelink channel, or long-range, using the cellular network (LTE or 5G). However, none of the technologies alone can support the expected variety of applications for a large number of vehicles, nor all the temporal and spatial requirements of connected and autonomous vehicles. Thus, it is proposed the collaborative or hybrid use of short-range communications, with lower latency, and of long-range technologies, potentially with higher latency, but integrating aggregated data of wider geographic scope. In this context, this work presents a hybrid vehicle communications model, capable of providing connectivity through two Radio Access Technologies (RAT), namely, ETSI ITS-G5 and LTE, to increase the probability of message delivery and, consequently, achieving a more robust, efficient and secure vehicle communication system. The implementation of short-range communication channels is done using Raw Packet Sockets, while the cellular connection is established using the Advanced Messaging Queuing Protocol (AMQP) protocol. The main contribution of this dissertation focuses on the design, implementation and evaluation of a Hybrid Routing Sublayer, capable of isolating messages that are formed/decoded from transmission/reception processes. This layer is, therefore, capable of managing traffic coming/destined to the application layer of intelligent transport systems (ITS), adapting and passing ITS messages between the highest layers of the protocol stack and the available radio access technologies. The Hybrid Routing Sublayer also reduces the financial costs due to the use of cellular communications and increases the efficiency of the use of the available electromagnetic spectrum, by introducing a cellular link controller using a Beacon Detector, which takes informed decisions related to the need to connect to a cellular network, according to different scenarios. The experimental results prove that hybrid vehicular communications meet the requirements of cooperative intelligent transport systems, by taking advantage of the benefits of both communication technologies. When evaluated independently, the ITS-G5 technology has obvious advantages in terms of latency over the LTE technology, while the LTE technology performs better than ITS-G5, in terms of throughput and reliability.As Comunicações Veiculares são um campo de pesquisa promissor, com um grande potencial de desenvolvimento de novas aplicações capazes de melhorar a segurança nas estradas, a eficiência do tráfego, bem com o conforto e entretenimento dos passageiros. As tecnologias de comunicação veícular podem ser de curto alcance, como por exemplo ETSI ITS-G5 ou o canal PC5 do 5G, ou de longo alcance, recorrendo à rede celular (LTE ou 5G). No entanto, nenhuma das tecnologias por si só, consegue suportar a variedade expectável de aplicações para um número de veículos elevado nem tampouco todos os requisitos temporais e espaciais dos veículos conectados e autónomos. Assim, é proposto o uso colaborativo ou híbrido de comunicações de curto alcance, com latências menores, e de tecnologias de longo alcance, potencialmente com maiores latências, mas integrando dados agregados de maior abrangência geográfica. Neste contexto, este trabalho apresenta um modelo de comunicações veiculares híbrido, capaz de fornecer conectividade por meio de duas Tecnologias de Acesso por Rádio (RAT), a saber, ETSI ITS-G5 e LTE, para aumentar a probabilidade de entrega de mensagens e, consequentemente, alcançar um sistema de comunicação veicular mais robusto, eficiente e seguro. A implementação de canais de comunicação de curto alcance é feita usando Raw Packet Sockets, enquanto que a ligação celular é estabelecida usando o protocolo Advanced Messaging Queuing Protocol (AMQP). A contribuição principal desta dissertação foca-se no projeto, implementação e avaliação de uma sub camada hibrída de encaminhamento, capaz de isolar mensagens que se formam/descodificam a partir de processos de transmissão/receção. Esta camadada é, portanto, capaz de gerir o tráfego proveniente/destinado à camada de aplicação de sistemas inteligentes de transportes (ITS) adaptando e passando mensagens ITS entre as camadas mais altas da pilha protocolar e as tecnologias de acesso rádio disponíveis. A sub camada hibrída de encaminhamento também potencia uma redução dos custos financeiros devidos ao uso de comunicações celulares e aumenta a eficiência do uso do espectro electromagnético disponível, ao introduzir um múdulo controlador da ligação celular, utilizando um Beacon Detector, que toma decisões informadas relacionadas com a necessidade de uma conexão a uma rede celular, de acordo com diferentes cenários. Os resultados experimentais comprovam que as comunicações veículares híbridas cumprem os requisitos dos sistemas cooperativos de transporte inteligentes, ao tirarem partido das vantagens de ambas tecnologias de comunicação. Quando avaliadas de forma independente, constata-se que que a tecnologia ITS-G5 tem vantagens evidentes em termos de latência sobre a tecnologia LTE, enquanto que a tecnologia LTE tem melhor desempenho que a LTE, ai nível de débito e fiabilidade.Mestrado em Engenharia Eletrónica e Telecomunicaçõe

Radio Communications

In the last decades the restless evolution of information and communication technologies (ICT) brought to a deep transformation of our habits. The growth of the Internet and the advances in hardware and software implementations modified our way to communicate and to share information. In this book, an overview of the major issues faced today by researchers in the field of radio communications is given through 35 high quality chapters written by specialists working in universities and research centers all over the world. Various aspects will be deeply discussed: channel modeling, beamforming, multiple antennas, cooperative networks, opportunistic scheduling, advanced admission control, handover management, systems performance assessment, routing issues in mobility conditions, localization, web security. Advanced techniques for the radio resource management will be discussed both in single and multiple radio technologies; either in infrastructure, mesh or ad hoc networks

Deep Learning Methods for Fingerprint-Based Indoor and Outdoor Positioning

Outdoor positioning systems based on the Global Navigation Satellite System have several shortcomings that have deemed their use for indoor positioning impractical. Location fingerprinting, which utilizes machine learning, has emerged as a viable method and solution for indoor positioning due to its simple concept and accurate performance. In the past, shallow learning algorithms were traditionally used in location fingerprinting. Recently, the research community started utilizing deep learning methods for fingerprinting after witnessing the great success and superiority these methods have over traditional/shallow machine learning algorithms. The contribution of this dissertation is fourfold: First, a Convolutional Neural Network (CNN)-based method for localizing a smartwatch indoors using geomagnetic field measurements is presented. The proposed method was tested on real world data in an indoor environment composed of three corridors of different lengths and three rooms of different sizes. Experimental results show a promising location classification accuracy of 97.77% with a mean localization error of 0.14 meter (m). Second, a method that makes use of cellular signals emitting from a serving eNodeB to provide symbolic indoor positioning is presented. The proposed method utilizes Denoising Autoencoders (DAEs) to mitigate the effects of cellular signal loss. The proposed method was evaluated using real-world data collected from two different smartphones inside a representative apartment of eight symbolic spaces. Experimental results verify that the proposed method outperforms conventional symbolic indoor positioning techniques in various performance metrics. Third, an investigation is conducted to determine whether Variational Autoencoders (VAEs) and Conditional Variational Autoencoders (CVAEs) are able to learn the distribution of the minority symbolic spaces, for a highly imbalanced fingerprinting dataset, so as to generate synthetic fingerprints that promote enhancements in a classifier\u27s performance. Experimental results show that this is indeed the case. By using various performance evaluation metrics, the achieved results are compared to those obtained by two state-of-the-art oversampling methods known as Synthetic Minority Oversampling TEchnique (SMOTE) and ADAptive SYNthetic (ADASYN) sampling. Fourth, a novel dataset of outdoor location fingerprints is presented. The proposed dataset, named OutFin, addresses the lack of publicly available datasets that researchers can use to develop, evaluate, and compare fingerprint-based positioning solutions which can constitute a high entry barrier for studies. OutFin is comprised of diverse data types such as WiFi, Bluetooth, and cellular signal strengths, in addition to measurements from various sensors including the magnetometer, accelerometer, gyroscope, barometer, and ambient light sensor. The collection area spanned four dispersed sites with a total of 122 Reference Points (RPs). Before OutFin was made available to the public, several experiments were conducted to validate its technical quality

Metabolic modelling and 13C flux analysis : application to biotechnologically important yeasts and a fungus

All bioconversions in cells derive from metabolism. Microbial metabolisms contain potential for bioconversions from simple source molecules to unlimited number of biochemicals and for degradation of even detrimental compounds. Metabolic fluxes are rates of consumption and production of compounds in metabolic reactions. Fluxes emerge as an ultimate phenotype of an organism from an integrated regulatory function of the underlying networks of complex and dynamic biochemical interactions. Since the fluxes are time-dependent, they have to be inferred from other, measurable, quantities by modelling and computational analysis. 13C-labelling is crucial for quantitative analysis of fluxes through intracellular alternative pathways. Local flux ratio analysis utilises uniform 13C-labelling experiments, where the carbon source contains a fraction of uniformly 13C-labelled molecules. Carbon-carbon bonds are cleaved and formed in metabolic reactions depending on the in vivo fluxes. 13C-labelling patterns of metabolites or macromolecule components can be detected by mass spectrometry (MS) or nuclear magnetic resonance (NMR) spectroscopy. Local flux ratio analysis utilises directly the 13C-labelling data and metabolic network models to solve ratios of converging fluxes. In this thesis the local flux ratio analysis has been extended and applied to analysis of phenotypes of biotechnologically important yeasts Saccharomyces cerevisiae and Pichia pastoris, and a fungus Trichoderma reesei. Oxygen dependence of in vivo net flux distribution of S. cerevisiae was quantified by using local flux ratios as additional constraints to the stoichiometric model of the central carbon metabolism. The distribution of fluxes in the pyruvate branching point turned out to be most responsive to different oxygen availabilities. The distribution of fluxes was observed to vary not only between the fully respiratory, respiro-fermentative and fermentative metabolic states but also between different respiro-fermentative states. The local flux ratio analysis was extended to the case of two-carbon source of glycerol and methanol co-utilisation by P. pastoris. The fraction of methanol in the carbon source did not have as profound effect on the distribution of fluxes as the growth rate. The effect of carbon catabolite repression (CCR) on fluxes of T. reesei was studied by reconstructing amino acid biosynthetic pathways and by performing local flux ratio analysis. T. reesei was observed to primarily utilise respiratory metabolism also in conditions of CCR. T. reesei metabolism was further studied and L-threo-3-deoxy-hexulosonate was identified as L-galactonate dehydratase reaction product by using NMR spectroscopy. L-galactonate dehydratase reaction is part of the fungal pathway for D-galacturonic acid catabolism

Production Scheduling

Generally speaking, scheduling is the procedure of mapping a set of tasks or jobs (studied objects) to a set of target resources efficiently. More specifically, as a part of a larger planning and scheduling process, production scheduling is essential for the proper functioning of a manufacturing enterprise. This book presents ten chapters divided into five sections. Section 1 discusses rescheduling strategies, policies, and methods for production scheduling. Section 2 presents two chapters about flow shop scheduling. Section 3 describes heuristic and metaheuristic methods for treating the scheduling problem in an efficient manner. In addition, two test cases are presented in Section 4. The first uses simulation, while the second shows a real implementation of a production scheduling system. Finally, Section 5 presents some modeling strategies for building production scheduling systems. This book will be of interest to those working in the decision-making branches of production, in various operational research areas, as well as computational methods design. People from a diverse background ranging from academia and research to those working in industry, can take advantage of this volume