O presente trabalho trata do planejamento da movimentação de contêineres vazios ao longo de um conjunto de portos, buscando o balanceamento entre as demandas e ofertas dos mesmos em todos os portos ao menor custo, e considerando as restrições de capacidade de transporte dos modais envolvidos. Para isso será adotado um modelo de fluxo em rede multi-produto para representar o sistema de movimentação de contêineres vazios e que servirá de base para o desenvolvimento de uma formulação matemática, a qual, implementada através de uma ferramenta computacional de otimização, determina os fluxos de vazios no sistema. A verificação do modelo proposto deu-se através de testes em problemas reduzidos de movimentação de vazios, assim como em um problema cujos resultados foram publicados na literatura. Os resultados sugeriram a adequabilidade e confiabilidade do modelo proposto que pode, então, ser aplicado a um problema real da empresa de navegação Hamburg Süd, tendo seus resultados comparados aos resultados fornecidos pela mesma. / This dissertation deals with the empty containers movement planning throughout a set of ports, aiming the balancing between the demands and supplies in all the ports at minimal cost, and considering the capacity constraints of the transport modes considered. A multi-commodity network flow model will be adopted to represent the empty containers movement system. This model supports the development of a mathematical formulation which, through a computational optimization tool, determines the flows of empty containers throughout the system. The verification of the proposed model was given through tests in reduced problems, as well as in a problem which results had already been published in literature. The results had suggested the adequateness and trustworthiness of the proposed model, which could, then, be applied to a real problem of the navigation company Hamburg Süd, and the results could be compared with the ones given by the company.

Esta pesquisa aborda o problema de alocação de jatos executivos compartilhados para casos em que a demanda diária é variável. É proposta uma ferramenta auxiliar de planejamento de uma empresa de operação de jatos compartilhados. São apresentadas as características principais do tipo de negócio que formam o problema estudado neste trabalho. Consideram-se os aspectos de uma empresa que administra jatos de propriedade compartilhada. O cliente adquire uma cota de uma aeronave e quando solicita uma viagem, com poucas horas de antecedência, a empresa deve garantir a realização do voo em uma aeronave da categoria adquirida. Também é de responsabilidade da empresa a gestão da tripulação, o reposicionamento da frota e a manutenção das aeronaves Este trabalho apresenta o desenvolvimento de uma ferramenta para auxiliar na tomada de decisões estratégicas que envolvem a escolha dos locais de base de operação e o dimensionamento da frota. A metodologia de solução é composta de um modelo de simulação e um de otimização. O modelo de simulação utiliza o método de Monte Carlo para obtenção da demanda de voos dia a dia que gera uma programação de clientes a atender. Os dados da simulação são então estruturados como um problema de fluxo em rede de mínimo custo e é realizada a alocação ótima das aeronaves. A ferramenta foi construída em ambiente de planilha eletrônica Microsoft Excel e aplicada em um caso prático de jatos executivos compartilhados com múltiplas bases. Foram testadas diversas configurações de bases e políticas operacionais como frota homogênea, frota heterogênea e frota alugada. Os resultados da ferramenta permitem determinar o impacto que a escolha das bases de operação tem no tamanho da frota e no reposicionamento de aeronaves. A metodologia mostrou-se robusta e, em tempo adequado, a ferramenta encontrou a solução ótima para cada configuração testada. / This research deals with the problem of scheduling jets with fractional ownership in cases where the demand varies daily. It has been devised a tool to support the planning phase of a company that operates shared jets. The main characteristics of the fractional shared market are presented in this manuscript and the research was developed under the point of view of a provider of fractional ownership. A client becomes a partial owner of an aircraft of a specific model and is entitled to a certain amount of flight hours. When the client requests a flight, usually only a few hours ahead, the fractional provider must guarantee that an aircraft of the requested model is available to the owner at the requested time and place. The provider is responsible for all the operational considerations, including managing the crew and having a well-maintained fleet. This work presents the development of a tool to help making decisions involving the choice of the operational bases and the size of the fleet. The solution methodology is composed of a simulation and a optimization model. Monte Carlo simulation is the method used to obtain the daily flight demand. The results of the simulation are structured as a minimum cost network flow problem to solve optimally the fleet allocation. This tool has been built in a Microsoft Excel spreadsheet environment and applied to a case of fractional jets with multiple bases. Several configurations and operational policies have been tested, such as operations with homogenous fleet, with heterogeneous fleet and with rented fleet. The results provided by the tool allow the user to evaluate the impact that the choice of the operational bases has on the size of the fleet and on the redeployment of the aircrafts. The methodology presented itself as adequate and the developed tool was able to solve optimally, in acceptable time, the problem for each case.

This work focuses on detection of denial of service (DoS) attacks which utilize random spoofing of source IP address in attack packets. These types of attacks lead to generation of side effect in a form of backscatter that can be used to identify victims of such attacks. Backscatter analysis has so far been limited to unused address space ranges referred to as network telescopes. This work therefore proposes a new method of DoS attack detection via backscatter outside of network telescope environment where legitimate user traffic is also present. Furthermore proposed approach uses only abstracted traffic in a form of network flows. Presented method was implemented as part of NEMEA system and tested on real flow data capture provided by CESNET.

This master‘s thesis focuses on distributed processing of big data from network communication. It begins with exploring network communication based on TCP/IP model with focus on data units on each layer, which is necessary to process during analyzation. In terms of the actual processing of big data is described programming model MapReduce, architecture of Apache Hadoop technology and it‘s usage for processing network flows on computer cluster. Second part of this thesis deals with design and following implementation of the application for processing network flows from network communication. In this part are discussed main and problematic parts from the actual implementation. After that this thesis ends with a comparison with available applications for network analysis and evaluation set of tests which confirmed linear growth of acceleration.

Cybersecurity has become an increasingly important concern for both military and civilian infrastructure globally. Because of the complexity that comes with wireless networks, adversaries have many means of infiltration and disruption of wireless networks. While there is much research done in defending these networks, understanding the robustness of these networks is tantamount for both designing new networks and examining possible security deficiencies in preexisting networks. This dissertation proposes to examine the robustness of wireless networks on three major fronts: the physical layer, the data-link layer, and the network layer. At the physical layer, denial-of-service jamming attacks are considered, and both additive interference and no interference are modeled in an optimal configuration and five common network topologies. At the data-link layer, data transmission efficacy and denial-of-sleep attacks are considered with the goal of maximizing throughput under a constrained lifetime. At the network layer, valid and anomalous communications are considered with the goal of classifying those anomalous communications apart from valid ones. This dissertation proposes that a thorough analysis of the aforementioned three layers provides valuable insights to robustness on general wireless networks.

Delay is known to be a critical performance metric for various real-world routing applications including multimedia communication and freight delivery. Provisioning delay-minimal (or at least delay-bounded) routing services for all traffic of an application is highly important. As a basic paradigm of networking, multi-path routing has been proven to be able to obtain lower delay performance than the single-path routing, since traffic congestions can be avoided. However, to our best knowledge, (i) many of existing delay-aware multi-path routing studies only consider the aggregate traffic delay. Considering that even the solution achieving the optimal aggregate traffic delay has a possibly unbounded delay performance for certain individual traffic unit, those studies may be insufficient in practice; besides, (ii) most existing studies which optimize or bound delays of all traffic are best-effort, where the achieved solutions have no theoretical performance guarantee. In this dissertation, we study four delay-aware multi-path routing problems, with the delay performances of all traffic taken into account. Three of them are in communication and one of them is in transportation. Note that our study differ from all related ones as we are the first to study the four fundamental problems to our best knowledge. Although we prove that our studied problems are all NP-hard, we design approximation algorithms with theoretical performance guarantee for solving each of them. To be specific, we claim the following contributions. Minimize maximum delay and average delay. First, we consider a single-unicast setting where in a multi-hop network a sender requires to use multiple paths to stream a flow at a fixed rate to a receiver. Two important delay metrics are the average sender-to-receiver delay and the maximum sender-to-receiver delay. Existing results say that the two delay metrics of a flow cannot be both within bounded-ratio gaps to the optimal. In comparison, we design three different flow solutions, each of which can minimize the two delay metrics simultaneously within a $(1/epsilon)$-ratio gap to the optimal, at a cost of only delivering $(1-epsilon)$-fraction of the flow, for any user-defined $epsilonin(0,1)$. The gap $(1/epsilon)$ is proven to be at least near-tight, and we further show that our solutions can be extended to the multiple-unicast setting. Minimize Age-of-Information (AoI). Second, we consider a single-unicast setting where in a multi-hop network a sender requires to use multiple paths to periodically send a batch of data to a receiver. We study a newly proposed delay-sensitive networking performance metric, AoI, defined as the elapsed time since the generation of the last received data. We consider the problem of minimizing AoI subject to throughput requirements, which we prove is NP-hard. We note that our AoI problem differs from existing ones in that we are the first to consider the batch generation of data and multi-path communication. We develop both an optimal algorithm with a pseudo-polynomial time complexity and an approximation framework with a polynomial time complexity. Our framework can build upon any polynomial-time $alpha$-approximation algorithm of the maximum delay minimization problem, to construct an $(alpha+c)$-approximate solution for minimizing AoI. Here $c$ is a constant dependent on throughput requirements. Maximize network utility. Third, we consider a multiple-unicast setting where in a multi-hop network there exist many network users. Each user requires a sender to use multiple paths to stream a flow to a receiver, incurring an utility that is a function of the experienced maximum delay or the achieved throughput. Our objective is to maximize the aggregate utility of all users under throughput requirements and maximum delay constraints. We observe that it is NP-complete either to construct an optimal solution under relaxed maximum delay constraints or relaxed throughput requirements, or to figure out a feasible solution with all constraints satisfied. Hence it is non-trivial even to obtain approximate solutions satisfying relaxed constraints in a polynomial time. We develop a polynomial-time approximation algorithm. Our algorithm obtains solutions with constant approximation ratios under realistic conditions, at the cost of violating constraints by up to constant-ratios. Minimize fuel consumption for a heavy truck to timely fulfill multiple transportation tasks. Finally, we consider a common truck operation scenario where a truck is driving in a national highway network to fulfill multiple transportation tasks in order. We study an NP-hard timely eco-routing problem of minimizing total fuel consumption under task pickup and delivery time window constraints. We note that optimizing task execution times is a new challenging design space for saving fuel in our multi-task setting, and it differentiates our study from existing ones under the single-task setting. We design a fast and efficient heuristic. We characterize conditions under which the solution of our heuristic must be optimal, and further prove its optimality gap in case the conditions are not met. We simulate a heavy-duty truck driving across the US national highway system, and empirically observe that the fuel consumption achieved by our heuristic can be $22%$ less than that achieved by the fastest-/shortest- path baselines. Furthermore, the fuel saving of our heuristic as compared to the baselines is robust to the number of tasks. / Doctor of Philosophy / We consider a network modeled as a directed graph, where it takes time for data to traverse each link in the network. It models many critical applications both in the communication area and in the transportation field. For example, both the European education network and the US national highway network can be modeled as directed graphs. We consider a scenario where a source node is required to send multiple (a set of) data packets to a destination node through the network as fast as possible, possibly using multiple source-to-destination paths. In this dissertation we study four problems all of which try to figure out routing solutions to send the set of data packets, with an objective of minimizing experienced travel time or subject to travel time constraints. Although all of our four problems are NP-hard, we design approximation algorithms to solve them and obtain solutions with theoretically bounded gaps as compared to the optimal. The first three problems are in the communication area, and the last problem is in the transportation field. We claim the following specific contributions. Minimize maximum delay and average delay. First, we consider the setting of simultaneously minimizing the average travel time and the worst (largest) travel time of sending the set of data packets from source to destination. Existing results say that the two metrics of travel time cannot be minimized to be both within bounded-ratio gaps to the optimal. As a comparison, we design three different routing solutions, each of which can minimize the two metrics of travel time simultaneously within a constant bounded ratio-gap to the optimal, but at a cost of only delivering a portion of the data. Minimize Age-of-Information (AoI). Second, we consider the problem of minimizing a newly proposed travel-time-sensitive performance metric, i.e., AoI, which is the elapsed time since the generation of the last received data. Our AoI study differs from existing ones in that we are the first to consider a set of data and multi-path routing. We develop both an optimal algorithm with a pseudo-polynomial time complexity and an approximation framework with a polynomial time complexity. Maximize network utility. Third, we consider a more general setting with multiple source destination pairs. Each source incurs a utility that is a function of the experienced travel time or the achieved throughput to send data to its destination. Our objective is to maximize the aggregate utility under throughput requirements and travel time constraints. We develop a polynomial-time approximation algorithm, at the cost of violating constraints by up to constant-ratios. It is non-trivial to design such algorithms, as we prove that it is NPcomplete either to construct an optimal solution under relaxed delay constraints or relaxed throughput requirements, or to figure out a feasible solution with all constraints satisfied. Minimize fuel consumption for a heavy truck to timely fulfill multiple transportation tasks. Finally, we consider a truck and multiple transportation tasks in order, where each task requires the truck to pick up cargoes at a source timely, and deliver them to a destination timely. The need of coordinating task execution times is a new challenging design space for saving fuel in our multi-task setting, and it differentiates our study from existing ones under the single-task setting. We design an efficient heuristic. We characterize conditions under which the solution of our heuristic must be optimal, and further prove its performance gap as compared to the optimal in case the conditions are not met.

Este trabalho apresenta um algoritmo determinístico para o planejamento da operação de sistemas hidrotérmicos de potência com representação individualizada das usinas hidroelétricas. Este problema caracteriza-se por ser não-linear, não diferenciável e de grande porte. O modelo de otimização foi baseado em algoritmos de fluxo em rede não-linear e foi utilizado o método do gradiente reduzido para se encontrar a direção ótima e o método da razão áurea para a busca do tamanho do passo ótimo. A estrutura da rede hidráulica formada pelas equações de balanço de água foi explorada através da definição da base na matriz defluência básica. Testes no programa foram realizados em diversos sistemas compostos por usinas reais pertencentes ao sistema sudeste brasileiro. Esses estudos foram realizados visando apresentar os princípios básicos que regem a operação ótima dos reservatórios e validar o algoritmo implementado. / This work presents a deterministic algorithm for the operational planning of hydrothermal power systems where each plant is represented individually. This problem is characterized by non-linear, non-diferenciable and large scale. The optimization model was based in non-linear network flow algorithm and it was used the reduced gradient method to find the optimal direction and the golden ratio method to find the best step size. The structure of hydraulic network formed by the water balance equation was exploited through the definition of the base in the basic flow matrix. Many tests were done with some system composed by real plants located on brazilian southeast. This studies was done to show the basics principles that rule the optimal operation of reservoirs and to validate the algorithm implemented.

A relevância da infraestrutura de transporte para incrementos em produtividade, induzindo ao desenvolvimento socioeconômico de determinada região é amplamente reconhecida. O Brasil, no entanto, apresenta sérias deficiências em relação à sua infraestrutura de transporte, oriundas de seu desenvolvimento histórico e da redução de níveis de investimentos públicos no setor nas últimas décadas. Estas deficiências traduzem-se em grande concentração no modal rodoviário para o transporte de cargas, menos eficiente do que os modais ferroviário e hidroviário, resultando em reduzida competitividade das organizações nacionais. Neste contexto, objetivou-se no presente trabalho a proposição de um modelo para avaliação e seleção de investimentos em infraestrutura de transporte de cargas, considerando-se seu caráter multidimensional. Para isso, foi proposta metodologia integrando os conceitos de análise de decisão multicritério e de programação matemática, representados pela teoria de utilidade multiatributo (Multi-Attribute Utility Theory - MAUT) e por problema de otimização de fluxos em rede (Minimum Cost Network Flow Problem - MCNFP), respectivamente. No desenvolvimento do modelo foram contemplados critérios de avaliação referentes às dimensões de análise financeira, operacional e ambiental. Posteriormente, foi considerada a aplicação de versões do modelo proposto com diferentes números de períodos de análise em caso ilustrativo, representativo da rede de transporte disponível e planejada da região Norte do Brasil. A aplicação das diversas versões do modelo proposto, de forma geral, apresentou resultados compatíveis com as teorias relacionadas à avaliação deste problema de decisão, incluindo indução à multimodalidade. Algumas versões do modelo apresentaram violações em algumas de suas restrições. Estes resultados adversos não foram plenamente eliminados, devido a limitações das ferramentas adotadas para aplicação. No entanto, foi possível a correção manual destas violações, resultando em soluções viáveis que, apesar de não serem consideradas ótimas, são mais completas do que soluções obtidas por meio de metodologias unidimensionais de análise. Por fim, foram apresentadas recomendações para condução de trabalhos futuros visando eliminação dos resultados adversos do modelo proposto e complementação de sua análise. / The role of transport infrastructure in productivity increases leading to regional social-economic development is widely recognized. Brazil, however, has serious deficiencies in its transport infrastructure, rooted in the country\'s historical development and in the recent decades\' reduction of public investment in the sector. These deficiencies can be observed in Brazil\'s strong focus on roads for cargo transportation, which besides being less efficient than rail and waterways, results in reduced competitiveness of national enterprises. In this context, the aim of this work was to propose a model for evaluating and selecting investments in freight\'s transportation infrastructure, considering its multidimensional character. It was proposed a methodology integrating the concepts of multi-criteria decision analysis and mathematical programming, represented by the Multi-Attribute Utility Theory (MAUT) along with the Minimum Cost Network Flow Problem (MCNFP). The developed model included financial, operational and environmental analysis evaluation criteria. Subsequently, this study applied the proposed model into a case study of the transportation network, available and planned, of the Northern region of Brazil. Overall, the application of various versions of the proposed model yielded results consistent with related evaluation and decision making theories, including induction of multimodality. Some versions of the model presented some violations of its restrictions. These adverse results were not fully eliminated due to the limitations of the application tools utilized. It was possible, however, to manually correct these violations and obtain viable solutions that, while cannot be considered optimal, are more complete than those obtained by single dimension analysis. Finally, recommendations were made for future studies aiming at eliminating the proposed model\'s adverse outcomes, and complementing its analysis.

Les terminaux à conteneurs utilisent les nouvelles technologies (EDI, RFID et GPS) pour échanger des données avec leurs partenaires, pour localiser les conteneurs et leurs équipements dans le terminal, et pour automatiser des tâches. Dans cette thèse, nous montrons comment ces informations peuvent être utilisées dans la gestion des opérations.La première partie utilise les informations sur les volumes annoncés pour affecter des ressources internes dans le but de minimiser le retard global au terminal. Nous représentons cette problématique à l'aide d'un problème de flot que nous implémentons comme programme linéaire mixte. Une étude de cas est réalisée pour un terminal du Grand Port Maritime de Marseille. En outre, nous combinons le problème d'affectation de ressources avec le dimensionnement d'un système de rendez-vous. Ceci permet de minimiser le retard global.La deuxième partie utilise les informations sur les conteneurs à retirer et leurs emplacements pour optimiser le déstockage. Le but est de retirer tous les conteneurs d'une rangée en minimisant le nombre de repositionnements parasites. Nous améliorons un modèle binaire, proposons une approche exacte de type branch and price - avec un sous-problème binaire et deux variantes d'un sous-problème énumératif - et en dérivons une approche heuristique - avec un sous-problème heuristique. L'approche exacte ne résout que les petites instances ; l'approche heuristique obtient des résultats satisfaisants mais devra être améliorée. Nous nous intéressons aussi à la version dynamique du problème où les informations sur les conteneurs à retirer arrivent petit à petit et comparons différentes stratégies de repositionnement. / Container terminals use intelligent freight technologies (e.g., EDI, RFID and GPS) to exchange data with their partners, to locate containers and equipment within the terminal, and to automate tasks. This thesis illustrated, via two examples, how this data may be used to optimize operations at the terminal.The first part uses information on announced volumes to allocate internal handling equipment. The objective is to minimize overall delays at the terminal. The problem is represented as a network flow problem and implemented as a linear mixed integer programming model. A case study for a terminal at the Grand Port Maritime de Marseille is carried out. We also showed that combining the allocation problem with the dimensioning of a truck appointment system may reduce overall delays at the terminal. The second part uses information on announced container retrievals and container positions to improve retrieval operations. The objective is to retrieve containers from a bay in a given sequence with a minimum number of parasite relocations. We improve an existing binary programming model and introduce an exact branch and price approach - with a binary subproblem and two variants of an enumerative subproblem - and a heuristic branch and price approach - with a heuristic subproblem. The exact approach solves only small instances; the heuristic approach performs well on several instances, but should be improved further. We also deal with a dynamic version of the problem where the retrieval order becomes revealed over time and evaluate different relocation strategies for this case.

No presente trabalho, fez-se a adaptação do reservatório superficial do ModSimLS para trabalhar como reservatório do solo. O modelo denomina-se IrrigaLS. Por comparação com o método do balanço hídrico, verificou-se que o IrrigaLS é apto para determinar demandas de irrigação suplementares e/ou totais. Com a adaptação, o modelo considera a produção agrícola como o resultado da interação dos fatores água-clima-planta-solo. A capacidade de simular sistemas complexos de recursos hídricos foi testada por comparação dos resultados do IrrigaLS com um modelo de simulação similar (ModSimLS). No ModSimLS, as demandas foram calculadas usando método tradicional de balanço hídrico. Verificou-se que o modelo é apto para simular sistemas complexos de recursos hídricos e apresenta algumas vantagens sobre o ModSimLS, quais sejam: determina a necessidade hídrica real da cultura; garante em períodos de seca um suprimento mínimo de água para a planta; garante uma economia de água pela inclusão da precipitação e possibilidade de variação do volume meta; diferencia as culturas com relação a sensibilidade ao déficit hídrico e calcula o balanço hídrico diário do solo. / In this work, an adaptation in the ModSimLS surface reservoir has been made in order to make it work as a soil reservoir. The model is called IrrigaLS. When compared to the water balance method, it was ascertained that IrrigaLS is suitable for determining supplementary and/or total irrigation demands. The model adaptation considers agricultural production as a result from water-weather-plant-soil factors interaction. The model capability to simulate complex water resources systems has been tested by comparing the results of IrrigaLS with a similar simulation model (ModSimLS) where the irrigation demands were computed using traditional water balance methods. It was ascertained that the model is suitable for simulating complex water resources systems and it has some advantages over ModSimLS, that are: it determines the real water needs of the culture; it guarantees a minimum water supply to the crop during dry periods, it guarantees water saving by the inclusion of rainfall and by the possibility to choose the soil moisture target; it distinguishes the crops in relation to the water deficit sensibility and it calculates the soil daily water balance.