A crescente complexidade das redes de comunicação de dados tem como conseqüência direta tornar cada vez mais complexas as tarefas de projetar seu dimensionamento e evolução. Um passo preliminar vitalmente importante no projeto de uma rede é a coleta de dados relacionados ao uso esperado da rede. Os padrões de tráfego estimados são usados nos cálculos de dimensionamento dos recursos. Fortemente relacionada a estas atividades está a previsão da performance em termos de throughput da rede, tempos de resposta, probabilidade de congestionamento, entre outras. Uma análise de performance efetiva depende de se representar precisamente a configuração da rede e da carga de tráfego a ela submetida. Técnicas de modelagem analítica ou de simulação podem ser usadas para determinar a performance esperada do sistema. Neste trabalho a usada a técnica de simulação para modelar o tráfego da rede usando dados coletados em uma rede real por monitoração. Trabalhando-se com o modelo validado e possível ajustar a carga de tráfego para representar mudanças esperadas nos volumes de tráfego, e testar o efeito na performance de diferentes configurações de rede. Isso possibilita que os processos de planejamento e projeto sejam executados com confiança, alem dos custos da rede poderem ser otimizados. O sistema apresentado neste trabalho e orientado à gerência de performance de redes, apoiando as atividades de gerência e planejamento de capacidade. Defende-se a idéia de que, a partir do perfil dos usuários de uma rede, derivado do tráfego por eles gerado, pode-se construir um modelo de tráfego significativamente representativo para a análise e previsão do desempenho da rede. O modelo foi desenvolvido para redes de comutação de pacotes com serviço orientado a conexão, e validado sobre o tráfego de uma rede X.25 através de um modelo de simulação, implementado em GPSS. O protótipo do sistema é composto por três processos principais que incorporam as etapas da análise de performance: monitoração do tráfego, análise do tráfego e simulação do tráfego. Na monitoração, são contabilizadas uma série de variáveis para cada conexão gerada na rede. Para cada tipo de aplicação são calculados os respectivos fatores de carga de tráfego. As aplicações são classificadas em dois grandes grupos: interativas e não-interativas. O processo de análise do tráfego gera os fatores de carga de tráfego na forma de tabelas e gráficos. As conexões e as métricas de performance produzidas na simulação do tráfego podem ser analisadas e validadas graficamente. O sistema proposto foi especificado em SDL (Specification and Description Language). / The increasing complexity of communication networks turns each time more complex the task to plan its expansion and evolution. A vitally important preliminar step in computer network design is the gathering of data relating to the expected use of the network. The estimated traffic patterns are used in resource usage computations. Closely related to these activities is the estimation of performance in terms of network throughput, response times, congestion probability, among others. An efective performance analysis requires the accurate representation of computer network configuration and traffic load. Analytical or simulation techniques can be used to establish the expected system performance. This work makes use of simulation to model the network traffic, based on collected data of a real network. network. Working with the validated model is possible to adjust the traffic load to represent future demand, and to test the performance impact under distinct network configurations. This enable a trustful execution of network planning and design, besides of the cost optimization. The system presented at this work is network performance management oriented, giving support to capacity management and capacity planning. The central idea is that, through network users profile achieved from generated traffic, it's possible to build a representative traffic model to aim at the network performance analysis and forecast. The model was developed to connection oriented packet switched networks, and validated by means of a simulation model to X.25 network traffic, implementd in GPSS. The system prototype comprises three process: traffic monitoring, traffic analysis and traffic simulation. In monitoring, a set of variables are registered for each network connection generated. The traffic load factors are computed according the application type. The applications are classified in two groups: interactive and non-interactive. The traffic analysis process produces traffic load factors in form of tables and graphics. Connections and performance metrics generated at traffic simulation can be graphically analyzed and validated. The proposed system was specified in SDL (Specification and Description Language).

A crescente complexidade das redes de comunicação de dados tem como conseqüência direta tornar cada vez mais complexas as tarefas de projetar seu dimensionamento e evolução. Um passo preliminar vitalmente importante no projeto de uma rede é a coleta de dados relacionados ao uso esperado da rede. Os padrões de tráfego estimados são usados nos cálculos de dimensionamento dos recursos. Fortemente relacionada a estas atividades está a previsão da performance em termos de throughput da rede, tempos de resposta, probabilidade de congestionamento, entre outras. Uma análise de performance efetiva depende de se representar precisamente a configuração da rede e da carga de tráfego a ela submetida. Técnicas de modelagem analítica ou de simulação podem ser usadas para determinar a performance esperada do sistema. Neste trabalho a usada a técnica de simulação para modelar o tráfego da rede usando dados coletados em uma rede real por monitoração. Trabalhando-se com o modelo validado e possível ajustar a carga de tráfego para representar mudanças esperadas nos volumes de tráfego, e testar o efeito na performance de diferentes configurações de rede. Isso possibilita que os processos de planejamento e projeto sejam executados com confiança, alem dos custos da rede poderem ser otimizados. O sistema apresentado neste trabalho e orientado à gerência de performance de redes, apoiando as atividades de gerência e planejamento de capacidade. Defende-se a idéia de que, a partir do perfil dos usuários de uma rede, derivado do tráfego por eles gerado, pode-se construir um modelo de tráfego significativamente representativo para a análise e previsão do desempenho da rede. O modelo foi desenvolvido para redes de comutação de pacotes com serviço orientado a conexão, e validado sobre o tráfego de uma rede X.25 através de um modelo de simulação, implementado em GPSS. O protótipo do sistema é composto por três processos principais que incorporam as etapas da análise de performance: monitoração do tráfego, análise do tráfego e simulação do tráfego. Na monitoração, são contabilizadas uma série de variáveis para cada conexão gerada na rede. Para cada tipo de aplicação são calculados os respectivos fatores de carga de tráfego. As aplicações são classificadas em dois grandes grupos: interativas e não-interativas. O processo de análise do tráfego gera os fatores de carga de tráfego na forma de tabelas e gráficos. As conexões e as métricas de performance produzidas na simulação do tráfego podem ser analisadas e validadas graficamente. O sistema proposto foi especificado em SDL (Specification and Description Language). / The increasing complexity of communication networks turns each time more complex the task to plan its expansion and evolution. A vitally important preliminar step in computer network design is the gathering of data relating to the expected use of the network. The estimated traffic patterns are used in resource usage computations. Closely related to these activities is the estimation of performance in terms of network throughput, response times, congestion probability, among others. An efective performance analysis requires the accurate representation of computer network configuration and traffic load. Analytical or simulation techniques can be used to establish the expected system performance. This work makes use of simulation to model the network traffic, based on collected data of a real network. network. Working with the validated model is possible to adjust the traffic load to represent future demand, and to test the performance impact under distinct network configurations. This enable a trustful execution of network planning and design, besides of the cost optimization. The system presented at this work is network performance management oriented, giving support to capacity management and capacity planning. The central idea is that, through network users profile achieved from generated traffic, it's possible to build a representative traffic model to aim at the network performance analysis and forecast. The model was developed to connection oriented packet switched networks, and validated by means of a simulation model to X.25 network traffic, implementd in GPSS. The system prototype comprises three process: traffic monitoring, traffic analysis and traffic simulation. In monitoring, a set of variables are registered for each network connection generated. The traffic load factors are computed according the application type. The applications are classified in two groups: interactive and non-interactive. The traffic analysis process produces traffic load factors in form of tables and graphics. Connections and performance metrics generated at traffic simulation can be graphically analyzed and validated. The proposed system was specified in SDL (Specification and Description Language).

The transport infrastructure facilitates the development of national economies not only in Europe but all over the world. Stagnating transport network development, along with stagnating modernisation of such networks caused by a lack of funds and associated with the absence of modern approach and technology within the construction and operation, has a fatal impact on the advancement of trade, industry and, ultimately, the development of the state itself. The dissertation thesis aims to describe and verify the way the heavy road infrastructure development supports the economy of the whole country, regions and economic entities. At the same time, the thesis strives to examine whether the construction completion accelerates the development and building of logistic centres in the vicinity of such big highways, and the manner the commissioning of such buildings is reflected in traffic intensity changes inland and at the borders.

Route planning forms an important aspect of airline operations for them to sustain the effects of deregulation and fierce competition. The Indian economic liberalization in 1991 has seen diminishing monopoly of Air India and dynamic demand splits amongst the service providers. Our research focuses on developing an aggregate route traffic demand forecasting (RTDF) model specifically for international carriers operating from India. The model is an econometric model that combines concepts of the traditional Gravity model of Physics and the Micro-economic theoretic model that links demand to price. In other words, the RTDF model is a fusion of the behavioral and gravity models. While developing the model, Becker’s approach of utility maximization has been made use of, thereby combining time and other inputs required to produce travel. The model is developed for the existing international routes from India with 2005 aggregative data provided by International Civil Aviation Organization (ICAO), which spanned 15 countries in Europe, Asia, Canada, and North America. The model has been validated and tested for its predictive power on a few intentionally left out routes from the original sample. The model explains about 70% of the variance, which is well above the acceptable zone for cross-sectional data. The model is then estimated for 2007 data on a few randomly selected high demand routes; the prediction error ranging from a minimum of 3.5% to a maximum of 13%, a range well within the acceptable error limits. We derive a sector-cost-model (SCM) by applying the concept of break-even analysis on the RTDF model. The SCM provides cost estimates on a particular route at various levels of airfare. The SCM helps us gain further insights into the business nature prevailing in the airline sector. On the viability of operations, we propose the sector-operation-fare (SOF) to be charged on a respective route, given the load factor, if the airline wishes to continue operations. For arriving at the SOF, we follow a demand oriented framework that comprises of two demand curves: the airline curve and the traffic curve. The numerical analyses provide room for policy formulations that help airlines in refining, redefining, and revitalizing the decision-making process in their operations. Airlines can use this model to forecast demand for a newly contemplated route and obtain a fair idea of the price they can charge the customer. In other words, airlines can estimate the economic viability of operations on a respective route.

Orientador: Lee Luan Ling / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação / Made available in DSpace on 2018-08-22T11:35:06Z (GMT). No. of bitstreams: 1 Chipana_AnaGloriaMamani_M.pdf: 2882297 bytes, checksum: e463366f676910239386bd95bd3a6753 (MD5) Previous issue date: 2012 / Resumo: Nesta dissertação se propõe um método de controle de admissão de chamadas fuzzy (FCAC) e um método de controle de fluxo fuzzy (FFC), considerando tráfegos multiclasses. Ambos métodos trabalham em conjunto e são implementados na interface aérea das redes 3G UMTS. O método FCAC aceita ou rejeita a requisição de uma nova chamada considerando a prioridade de cada classe de tráfego, assim como a banda efetiva total disponível na interface aérea. Devido a natureza de controle fuzzy, o método FCAC-FFC proposto é considerado como um método de bloqueio gradual. Os usuários de menor prioridade serão sempre os primeiros a serem bloqueados se a banda efetiva total disponível não for suficiente. O método FFC reduz a taxa de transmissão dos usuários ativos de menor prioridade caso seja necessário e, como consequência, a banda efetiva disponível aumenta. Desta forma, temos um uso mais eficiente dos recursos do sistema incrementando o número médio de usuários ativos. O método proposto foi implementado no ambiente de simulação MATLAB e foi utilizada a toolbox de lógica fuzzy para projetar os controladores fuzzy. Os resultados da simulação mostram que o esquema de controle de admissão proposto garante o uso eficiente dos recursos da interface aérea e obtém um melhor desempenho em comparação com os esquemas CAC-FC e FCAC-FC analisados, em termos de probabilidade de bloqueio total / Abstract: This dissertation proposes a fuzzy call admission control method (FCAC) and a fuzzy flow control method (FFC) for multi-class traffic. Two methods should be used on the air interface of 3G UMTS networks. The FCAC method accepts or rejects a new call evaluating the priority of the input traffic class and the total effective bandwidth available at the air interface. Due to inherited fuzzy characteristics the proposed FCAC-FFC can be considered as a soft-blocking approach. The calls with lowest priority are blocked first whenever the currently available bandwidth is not large enough. The FFC method can reduce the transmission rates of active users of lower priority if necessary and consequently increases the effective bandwidth available. Therefore, the more efficient use of system transmission resource can be achieved by increasing the average number of active users. The proposed method was implemented in MATLAB environment, and the fuzzy logic toolbox was used to design the fuzzy controllers. The simulation results show that the proposed call admission control method guarantees efficient use of the air interface resource and achieves lower call blocking probability than the CAC-FC and FCAC-FC methods / Mestrado / Telecomunicações e Telemática / Mestra em Engenharia Elétrica

This diploma thesis deals with a proposal and a comparison of several options of transportation planning in the shopping area in the urban area of the town of Modřice, which is enlarging due to the building-up of new commercial centres. The first part of the thesis consists of a treatise on the field of traffic engineering, road-traffic telematics and ITS. The core of the work is formed by a detailed analysis of the current state and calibration of the transport simulation system AIMSUN. The following part shows three different ways of transportation in the given area and all of them include a model of the particular area made in the program AIMSUN and an elaborate analysis of the proposed solution. In the last part of the work all the proposed solutions are compared according to the results gained from the AIMSUN model.

In my diploma thesis, I applied IT model by Aimsun software on the traffic situation in the city of Blansko. I created my own model showing positives and negatives of planned bridge project across the river Svitava and the railroad corridor applying available information and documents regarding the project and my own data in this specific area. This overpass shall improve the traffic situation in the city of Blansko because mentioned bridge project shall be the second connection of two parts of the city of Blansko that is split by the river of Svitava. In this thesis, I apply the bridge project on the current traffic situation assuming that the bridge project will be implemented in 3 years. I deal with the situation in the city of Blansko with and without implementation of the bridge project.

Travel-time information is essential in Advanced Traveler Information Systems (ATISs) and Advanced Traffic Management Systems (ATMSs). A key component of these systems is the prediction of the spatiotemporal evolution of roadway traffic state and travel time. From the perspective of travelers, such information can result in better traveler route choice and departure time decisions. From the transportation agency perspective, such data provide enhanced information with which to better manage and control the transportation system to reduce congestion, enhance safety, and reduce the carbon footprint of the transportation system. The objective of the research presented in this dissertation is to develop a framework that includes three major categories of methodologies to predict the spatiotemporal evolution of the traffic state. The proposed methodologies include macroscopic traffic modeling, computer vision and recursive probabilistic algorithms. Each developed method attempts to predict traffic state, including roadway travel times, for different prediction horizons. In total, the developed multi-tool framework produces traffic state prediction algorithms ranging from short – (0~5 minutes) to medium-term (1~4 hours) considering departure times up to an hour into the future. The dissertation first develops a particle filter approach for use in short-term traffic state prediction. The flow continuity equation is combined with the Van Aerde fundamental diagram to derive a time series model that can accurately describe the spatiotemporal evolution of traffic state. The developed model is applied within a particle filter approach to provide multi-step traffic state prediction. The testing of the algorithm on a simulated section of I-66 demonstrates that the proposed algorithm can accurately predict the propagation of shockwaves up to five minutes into the future. The developed algorithm is further improved by incorporating on- and off-ramp effects and more realistic boundary conditions. Furthermore, the case study demonstrates that the improved algorithm produces a 50 percent reduction in the prediction error compared to the classic LWR density formulation. Considering the fact that the prediction accuracy deteriorates significantly for longer prediction horizons, historical data are integrated and considered in the measurement update in the developed particle filter approach to extend the prediction horizon up to half an hour into the future. The dissertation then develops a travel time prediction framework using pattern recognition techniques to match historical data with real-time traffic conditions. The Euclidean distance is initially used as the measure of similarity between current and historical traffic patterns. This method is further improved using a dynamic template matching technique developed as part of this research effort. Unlike previous approaches, which use fixed template sizes, the proposed method uses a dynamic template size that is updated each time interval based on the spatiotemporal shape of the congestion upstream of a bottleneck. In addition, the computational cost is reduced using a Fast Fourier Transform instead of a Euclidean distance measure. Subsequently, the historical candidates that are similar to the current conditions are used to predict the experienced travel times. Test results demonstrate that the proposed dynamic template matching method produces significantly better and more stable prediction results for prediction horizons up to 30 minutes into the future for a two hour trip (prediction horizon of two and a half hours) compared to other state-of-the-practice and state-of-the-art methods. Finally, the dissertation develops recursive probabilistic approaches including particle filtering and agent-based modeling methods to predict travel times further into the future. Given the challenges in defining the particle filter time update process, the proposed particle filtering algorithm selects particles from a historical dataset and propagates particles using data trends of past experiences as opposed to using a state-transition model. A partial resampling strategy is then developed to address the degeneracy problem in the particle filtering process. INRIX probe data along I-64 and I-264 from Richmond to Virginia Beach are used to test the proposed algorithm. The results demonstrate that the particle filtering approach produces less than a 10 percent prediction error for trip departures up to one hour into the future for a two hour trip. Furthermore, the dissertation develops an agent-based modeling approach to predict travel times using real-time and historical spatiotemporal traffic data. At the microscopic level, each agent represents an expert in the decision making system, which predicts the travel time for each time interval according to past experiences from a historical dataset. A set of agent interactions are developed to preserve agents that correspond to traffic patterns similar to the real-time measurements and replace invalid agents or agents with negligible weights with new agents. Consequently, the aggregation of each agent's recommendation (predicted travel time with associated weight) provides a macroscopic level of output – predicted travel time distribution. The case study demonstrated that the agent-based model produces less than a 9 percent prediction error for prediction horizons up to one hour into the future. / Ph. D.

This thesis concerns measuring, understanding and modelling Internet traffic. We first study the origins of the statistical properties of Internet traffic, in particular its scaling behaviour, and propose a constructive model of packet traffic with physically motivated parameters. We base our analysis on a large amount of empirical data measured on different networks, and use a so called semi-experimental approach to isolate certain features of traffic we seek to model. These results lead to the choice of a particular Poisson cluster process, known as Bartlett-Lewis point process, for a new packet traffic model. This model has a small number of parameters with simple networking meaning, and is mathematically tractable. It allows us to gain valuable insight on the underlying mechanisms creating the observed statistics. / In practice, Internet traffic measurements are limited by the very large amount of data generated by high bandwidth links. This leads us to also investigate traffic sampling strategies and their respective inversion methods. We argue that the packet sampling mechanism currently implemented in Internet routers is not practical when one wants to infer the statistics of the full traffic from partial measurements. We advocate the use of flow sampling for many purposes. We show that such sampling strategy is much easier to invert and can give reasonable estimates of higher order traffic statistics such as distribution of number of packets per flow and spectral density of the packet arrival process. This inversion technique can also be used to fit the Bartlett-Lewis point process model from sampled traffic. / We complete our understanding of Internet traffic by focusing on the small scale behaviour of packet traffic. To do so, we use data from a fully instrumented Tier-1 router and measure the delays experienced by all the packets crossing it. We present a simple router model capable of simply reproducing the measured packet delays, and propose a scheme to export router performance information based on busy periods statistics. We conclude this thesis by showing how the Bartlett-Lewis point process can model the splitting and merging of packet streams in a router.

This study was created to describe and to design the 3D simulator for a driving schools. In the study there are gathered the basic definitions of available simulators and possibilities of their application in real life. This new simulator is designed on a basis of detailed study of available simulators. In study are described the issues with simulation of traffic system, monitoring compliance with the traffic rules as well as a new user interface model. The whole concept and procedure during implementation of the simulator are described at the end of the work.