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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
11

Meta-heurísticas baseadas em busca em vizinhança variável aplicadas a problemas de operação de transportes. / Metaheuristic based on variable neighbourhood search applied to operation transport problems.

Reis, Jorge Von Atzingen dos 30 September 2013 (has links)
Esta pesquisa trata da aplicação de meta-heurísticas baseadas em busca em vizinhança variável em problemas de operação de transportes. Desta forma, buscou-se encontrar problemas complexos durante a operação de sistemas de transportes, nas grandes cidades, que possam ser resolvidos com a aplicação de meta-heurística baseada em busca em vizinhança variável. Este trabalho aborda dois diferentes problemas de planejamento e operação de transportes. O primeiro problema abordado neste trabalho é o Problema de Programação da Tabela de Horários, de Veículos e de Tripulantes de Ônibus, no qual as viagens que comporão a tabela de horários, os veículos que executarão as viagens e as tripulações que operarão os veículos são alocadas simultaneamente e de maneira integrada. O segundo problema a ser abordado é o problema de distribuição física, o qual envolve o agrupamento e a alocação de entregas a uma frota de veículos visando minimizar o frete total. Uma abordagem para a modelagem matemática deste problema é modelar como um problema de bin-packing, com bins de tamanho variável unidimensional (do inglês Variable Sized Bin-Packing Problem - VSBPP), ou seja, uma generalização do tradicional problema de bin-packing no qual bins (veículos) de diferentes capacidades e custos estão disponíveis para a alocação de um conjunto de objetos (cargas), de modo que o custo total dos bins (veículos) utilizados seja mínimo. A outra abordagem proposta para o problema de distribuição física é modelar o problema como um problema de bin-packing, com bins de tamanho variável bidimensional (do inglês Bidimensional Variable Sized Bin-Packing Problem BiD-VSBPP). Assim sendo, trata-se de uma expansão do problema de bin-packing com bins de tamanho variável unidimensional (VSBPP), no qual bins (veículos) de diferentes capacidades (capacidade volumétrica e capacidade de carga) e custos estão disponíveis para a alocação de um conjunto de objetos (cargas), os quais possuem as dimensões peso e volume, de modo que o custo total dos bins (veículos) utilizados seja mínimo. Durante a realização deste trabalho, foi desenvolvido um programa computacional em C++, o qual implementa a meta-heurística Busca em Vizinhança Variável (VNS) e duas meta-heurísticas baseadas em VNS. São apresentados resultados de experimentos computacionais com dados reais e dados benchmarking. Os resultados obtidos comprovam a eficácia das meta-heurísticas propostas. / This work approaches variable neighborhood search meta-heuristic applicate on transport operation problems. This way, we sought find complex transport operation problems in large cities that can be solved with the variable neighborhood search meta-heuristic application. This work approaches two different transport planning and operation problems. The first problem approached in this paper is the Bus Timetable Vehicle Crew Scheduling Problem, in which timetabling, bus and crew schedules are simultaneously determined in an integrated approach. The second problem to be approached is the physical distribution problem which comprises grouping and assigning deliveries to a heterogeneous fleet of vehicles aiming to minimize the total freight cost. The problem can be mathematical modeled as one-dimensional Variable Sized Bin-Packing Problem (VSBPP), a generalization of the traditional bin-packing problem, in which bins (vehicles) with different sizes and costs are available for the assignment of the objects (deliveries) such that the total cost of the used bins (vehicles) is minimized. Another proposed approach to the problem of physical distribution is model as two dimensional Variable Sized Bin-Packing Problem (BiD-VSBPP). Therefore, it is an expansion of the bin-packing problem with bins variable-length-dimensional (VSBPP), in which bins (vehicle) of different capacity (capacity and load carrying capacity) and costs are available for allocation a set of objects (loads), which have the dimensions weight and volume, so that minimized the total cost of bins (vehicle). In this work, was developed a C++ software implemented, which was implemented a meta-heuristic Variable Neighborhood Search (VNS) and two others meta-heuristics based on VNS. Computational results for real-world problems and benchmarking problems are presented, showing the effectiveness of these proposed meta-heuristics.
12

Scalable cost-efficient placement and chaining of virtual network functions / Posicionamento e encadeamento escalável e baixo custo de funções virtualizados de rede

Luizelli, Marcelo Caggiani January 2017 (has links)
A Virtualização de Funções de Rede (NFV – Network Function Virtualization) é um novo conceito arquitetural que está remodelando a operação de funções de rede (e.g., firewall, gateways e proxies). O conceito principal de NFV consiste em desacoplar a lógica de funções de rede dos dispositivos de hardware especializados e, desta forma, permite a execução de imagens de software sobre hardware de prateleira (COTS – Commercial Off-The-Shelf). NFV tem o potencial para tornar a operação das funções de rede mais flexíveis e econômicas, primordiais em ambientes onde o número de funções implantadas pode chegar facilmente à ordem de centenas. Apesar da intensa atividade de pesquisa na área, o problema de posicionar e encadear funções de rede virtuais (VNF – Virtual Network Functions) de maneira escalável e com baixo custo ainda apresenta uma série de limitações. Mais especificamente, as estratégias existentes na literatura negligenciam o aspecto de encadeamento de VNFs (i.e., objetivam sobretudo o posicionamento), não escalam para o tamanho das infraestruturas NFV (i.e., milhares de nós com capacidade de computação) e, por último, baseiam a qualidade das soluções obtidas em custos operacionais não representativos. Nesta tese, aborda-se o posicionamento e o encadeamento de funções de rede virtualizadas (VNFPC – Virtual Network Function Placement and Chaining) como um problema de otimização no contexto intra- e inter-datacenter. Primeiro, formaliza-se o problema VNFPC e propõe-se um modelo de Programação Linear Inteira (ILP) para resolvêlo. O objetivo consiste em minimizar a alocação de recursos, ao mesmo tempo que atende aos requisitos e restrições de fluxo de rede. Segundo, aborda-se a escalabilidade do problema VNFPC para resolver grandes instâncias do problema (i.e., milhares de nós NFV). Propõe-se um um algoritmo heurístico baseado em fix-and-optimize que incorpora a meta-heurística Variable Neighborhood Search (VNS) para explorar eficientemente o espaço de solução do problema VNFPC. Terceiro, avalia-se as limitações de desempenho e os custos operacionais de estratégias típicas de aprovisionamento ambientes reais de NFV. Com base nos resultados empíricos coletados, propõe-se um modelo analítico que estima com alta precisão os custos operacionais para requisitos de VNFs arbitrários. Quarto, desenvolve-se um mecanismo para a implantação de encadeamentos de VNFs no contexto intra-datacenter. O algoritmo proposto (OCM – Operational Cost Minimization) baseia-se em uma extensão da redução bem conhecida do problema de emparelhamento ponderado (i.e., weighted perfect matching problem) para o problema de fluxo de custo mínimo (i.e., min-cost flow problem) e considera o desempenho das VNFs (e.g., requisitos de CPU), bem como os custos operacionais estimados. Os resultados alcaçados mostram que o modelo ILP proposto para o problema VNFPC reduz em até 25% nos atrasos fim-a-fim (em comparação com os encadeamentos observados nas infra-estruturas tradicionais) com um excesso de provisionamento de recursos aceitável – limitado a 4%. Além disso, os resultados evidenciam que a heurística proposta (baseada em fix-and-optimize) é capaz de encontrar soluções factíveis de alta qualidade de forma eficiente, mesmo em cenários com milhares de VNFs. Além disso, provê-se um melhor entendimento sobre as métricas de desempenho de rede (e.g., vazão, consumo de CPU e capacidade de processamento de pacotes) para as estratégias típicas de implantação de VNFs adotadas infraestruturas NFV. Por último, o algoritmo proposto no contexto intra-datacenter (i.e. OCM) reduz significativamente os custos operacionais quando comparado aos mecanismos de posicionamento típicos uti / Network Function Virtualization (NFV) is a novel concept that is reshaping the middlebox arena, shifting network functions (e.g. firewall, gateways, proxies) from specialized hardware appliances to software images running on commodity hardware. This concept has potential to make network function provision and operation more flexible and cost-effective, paramount in a world where deployed middleboxes may easily reach the order of hundreds. Despite recent research activity in the field, little has been done towards scalable and cost-efficient placement & chaining of virtual network functions (VNFs) – a key feature for the effective success of NFV. More specifically, existing strategies have neglected the chaining aspect of NFV (focusing on efficient placement only), failed to scale to hundreds of network functions and relied on unrealistic operational costs. In this thesis, we approach VNF placement and chaining as an optimization problem in the context of Inter- and Intra-datacenter. First, we formalize the Virtual Network Function Placement and Chaining (VNFPC) problem and propose an Integer Linear Programming (ILP) model to solve it. The goal is to minimize required resource allocation, while meeting network flow requirements and constraints. Then, we address scalability of VNFPC problem to solve large instances (i.e., thousands of NFV nodes) by proposing a fixand- optimize-based heuristic algorithm for tackling it. Our algorithm incorporates a Variable Neighborhood Search (VNS) meta-heuristic, for efficiently exploring the placement and chaining solution space. Further, we assess the performance limitations of typical NFV-based deployments and the incurred operational costs of commodity servers and propose an analytical model that accurately predict the operational costs for arbitrary service chain requirements. Then, we develop a general service chain intra-datacenter deployment mechanism (named OCM – Operational Cost Minimization) that considers both the actual performance of the service chains (e.g., CPU requirements) as well as the operational incurred cost. Our novel algorithm is based on an extension of the well-known reduction from weighted matching to min-cost flow problem. Finally, we tackle the problem of monitoring service chains in NFV-based environments. For that, we introduce the DNM (Distributed Network Monitoring) problem and propose an optimization model to solve it. DNM allows service chain segments to be independently monitored, which allows specialized network monitoring requirements to be met in a efficient and coordinated way. Results show that the proposed ILP model for the VNFPC problem leads to a reduction of up to 25% in end-to-end delays (in comparison to chainings observed in traditional infrastructures) and an acceptable resource over-provisioning limited to 4%. Also, we provide strong evidences that our fix-and-optimize based heuristic is able to find feasible, high-quality solutions efficiently, even in scenarios scaling to thousands of VNFs. Further, we provide indepth insights on network performance metrics (such as throughput, CPU utilization and packet processing) and its current limitations while considering typical deployment strategies. Our OCM algorithm reduces significantly operational costs when compared to the de-facto standard placement mechanisms used in Cloud systems. Last, our DNM model allows finer grained network monitoring with limited overheads. By coordinating the placement of monitoring sinks and the forwarding of network monitoring traffic, DNM can reduce the number of monitoring sinks and the network resource consumption (54% lower than a traditional method).
13

Planejamento da expansão de sistemas de distribuição de energia elétrica considerando restauração do fornecimento /

Possagnolo, Leonardo Henrique Faria Macedo. January 2019 (has links)
Orientador: Rubén Augusto Romero Lázaro / Resumo: A grande maioria dos sistemas de distribuição de energia elétrica opera de forma radial. Isso significa que cada carga é alimentada por apenas uma subestação por meio de um único caminho. Entretanto, as redes de distribuição apresentam estrutura malhada, de forma que, caso uma contingência ocorra, o restabelecimento do fornecimento possa ser realizado para o maior número possível de consumidores. Os trabalhos que lidam com o problema de planejamento da expansão de sistemas de distribuição, no entanto, geralmente consideram a expansão do sistema para apenas uma topologia radial, sem levar em conta aspectos da restauração do fornecimento para melhoria dos índices de confiabilidade. Nesse contexto, este trabalho aborda o planejamento de sistemas de distribuição considerando aspectos econômicos e de confiabilidade, de forma a incluir a restauração do fornecimento no problema de planejamento da expansão. Na formulação do problema considera-se a expansão de novas subestações, o reforço de subestações existentes, a construção de novos alimentadores em novos caminhos, a troca de condutores existentes e a alocação de geradores distribuídos, além de expansão multiestágio e restauração do fornecimento para melhoria dos índices de confiabilidade. Dois métodos alternativos são propostos para resolver o problema descrito: o primeiro considera modelos matemáticos com diversos graus de precisão, para serem resolvidos por métodos exatos, e o segundo é uma meta-heurística de busca e vizinhança... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The vast majority of electricity distribution systems are operated radially. This means that each load is supplied by only one substation through a single path. However, distribution networks have a meshed structure so that, in the case of a contingency, the supply is restored to as many customers as possible. The works that deal with the distribution systems expansion planning problem, however, generally consider the expansion of the system for only one radial topology, disregarding the restoration aspects to improve reliability indices. In this context, this work deals with the planning of distribution systems considering economic and reliability aspects, to include the service restoration in the planning problem. In the formulation of the problem, it is considered the expansion of new substations, the reinforcement of existing substations, the construction of new feeders in new paths, the exchange of existing conductors, and the allocation of distribution generation, besides multistage expansion and service restoration to improve the reliability indices of the system. Two alternative methods are proposed to solve the described problem: the first one considers relaxed or approximated mathematical models to be solved by exact methods, and the second one is a variable neighborhood search metaheuristic, which solves the complete model for the problem approximately, without guarantee of optimality. The initial solution of the metaheuristic is generated by a strategy that constr... (Complete abstract click electronic access below) / Doutor
14

Méthodes de modélisation et d'optimisation par recherche à voisinages variables pour le problème de collecte et de livraison avec transbordement / Modeling method and optimization by the variable neighborhood search for the pickup and delivery problem with transshipment

Tchapnga Takoudjou, Rodrigue 12 June 2014 (has links)
La présente thèse se déroule dans le cadre du projet ANR PRODIGE et est axée sur la recherche de stratégies permettant l’optimisation du transport en général et du transport routier de marchandises en particulier. Le problème de transport support de cette étude est le problème de collecte et livraison avec transbordement. Ce problème généralise plusieurs problèmes de transports classiques. Le transbordement y est utilisé comme levier de flexibilité et d’optimisation. Pour analyser et résoudre ce problème, les analyses sont effectuées suivant trois axes : le premier axe concerne l’élaboration d’un modèle analytique plus précisément d’un modèle mathématique en variables mixtes. Ce modèle permet de fournir dessolutions optimales au décisionnaire du transport mais présente l’inconvénient de nécessiter un temps de résolution qui croit exponentiellement avec la taille du problème. Cette limitation est levée par le deuxième axe d’étude qui permet de résoudre le problème de transport étudié par une méthode d’optimisation approchée tout en garantissant des solutions satisfaisantes.La méthode utilisée est une métaheuristique inspirée de la recherche à voisinages variables (VNS). Dans le troisième axe, l’ensemble des résultats obtenus dans la thèse sont testés en situation de transports réels via le projet PRODIGE. / The thesis is conducted under the ANR project PRODIGE and it is focused on seeking strategies allowing the optimization of transport in general and road freight transport in particular. The transportation problem support for this study is the pickup and delivery problem with transshipment.This problem generalizes several classical transportation problems.Transshipment is used as optimization and flexibility leverage. To study and solve this problem, analyzes are performed along three axes :the first objective concerns the development of an analytical model, more accurately a mathematical model with mixed variables. This model allows providing optimal solution to the decision maker, but has the disadvantage of requiring a time resolution that grows exponentially with the size of the problem. This limitation is overcome by the second line of the study that solves the transportation problem studied by an approximate optimization method while ensuring satisfactory solutions. The method used is a mataheuristic broadly followed the variables neighborhoods research principles. In the third objective, the overall results obtained in the thesis are tested in real transport situation via the PRODIGE project.
15

Models and algorithms for the combinatorial optimization of WLAN-based indoor positioning system / Modèles et algorithmes pour l'optimisation combinatoire de systèmes de localisation indoor basés sur les WLAN

Zheng, You 20 April 2012 (has links)
La localisation des personnes et des objets à l’intérieur des bâtiments basée sur les réseaux WLAN connaît un intérêt croissant depuis quelques années ; ce système peut être un parfait complément pour fournir des informations de localisation statique ou dynamique dans des environnements où les techniques de positionnement telles que GPS ne sont pas efficaces. Le manuscrit de thèse propose une nouvelle approche pour définir un système WLAN de positionnement indoor (WLAN-IPS) comme un problème d'optimisation combinatoire afin de garantir à la fois une qualité de communication et une minimisation de l'erreur de positionnement via le réseau. Cette approche est caractérisée par plusieurs questions difficiles que nous abordons en trois étapes.Dans un premier temps, nous avons conçu un réseau WLAN-IPS et mis en œuvre une plateforme de test. Nous avons examiné la performance du système sous diverses contraintes expérimentales et nous nous sommes penchés sur l'analyse des relations entre l'erreur de positionnement et les facteurs environnementaux externes. Ces relations ont permis de proposer des indicateurs pour évaluer l'erreur de positionnement. Ensuite nous avons proposé un modèle physique qui définit tous les paramètres majeurs rencontrés en WLAN-IPS à partir de la littérature. L'objectif initial des infrastructures WLAN étant de fournir un accès radio de qualité au réseau, nous avons introduit un objectif supplémentaire qui est de minimiser l'erreur de localisation dans le contexte IPS. Deux indicateurs principaux ont été définis afin d'évaluer la qualité de service (QoS) et l'erreur de localisation pour LBS (Location-Based Services). Enfin après avoir défini la formulation mathématique du problème d'optimisation et les indicateurs clés de performance, nous avons proposé un algorithme mono-objectif et un algorithme multicritère basés sur Tabu Search et Variable Neighborhood Search pour fournir des bonnes solutions en temps raisonnable. Les simulations montrent que ces deux algorithmes sont très efficaces pour le problème d'optimisation que nous avons posé. / Indoor Positioning Systems (IPS) using the existing WLAN have won growing interest in the last years, it can be a perfect supplement to provide location information of users in indoor environments where other positioning techniques such as GPS, are not much effective. The thesis manuscript proposes a new approach to define a WLAN-based indoor positioning system (WLAN-IPS) as a combinatorial optimization problem to guarantee the requested communication quality while optimizing the positioning error. This approach is characterised by several difficult issues we tackled in three steps.At first, we designed a WLAN-IPS and implemented it as a test framework. Using this framework, we looked at the system performance under various experimental constraints. Through these experiments, we went as far as possible in analysing the relationships between the positioning error and the external environmental factors. These relationships were considered as evaluation indicators of the positioning error. Secondly, we proposed a model that defines all major parameters met in the WLAN-IPS from the literature. As the original purpose of the WLAN infrastructures is to provide radio communication access, we introduced an additional purpose which is to minimize the location error within IPS context. Two main indicators were defined in order to evaluate the network Quality of Service (QoS) and the positioning error for Location-Based Service (LBS). Thirdly, after defining the mathematical formulation of the optimisation problem and the key performance indicators, we proposed a mono-objective algorithm and a multi-objective algorithm which are based on Tabu Search metaheuristic to provide good solutions within a reasonable amount of time. The simulations demonstrate that these two algorithms are highly efficient for the indoor positioning optimization problem.
16

Flexible Radio Resource Management for Multicast Multimedia Service Provision : Modeling and Optimization / Allocation de ressources radio pour les services multimédias : modélisation et optimisation

Xu, Qing 29 August 2014 (has links)
Le conflit entre la demande de services multimédia en multidiffusion à haut débit (MBMS) et les limites en ressources radio demandent une gestion efficace de l'allocation des ressources radio (RRM) dans les réseaux 3G UMTS. À l'opposé des travaux existant dans ce domaine, cette thèse se propose de résoudre le problème de RRM dans les MBMS par une approche d’optimisation combinatoire. Le travail commence par une modélisation formelle du problème cible, désigné comme Flexible Radio Resource Management Model (F2R2M). Une analyse de la complexité et du paysage de recherche est effectuée à partir de ce modèle. Tout d’abord on montre qu'en assouplissant les contraintes de code OVSF, le problème de RRM pour les MBMS peut s'apparenter à un problème de sac à dos à choix multiples (MCKP). Une telle constatation permet de calculer les limites théoriques de la solution en résolvant le MCKP similaire. En outre, l'analyse du paysage montre que les espaces de recherche sont accidentés et constellés d'optima locaux. Sur la base de cette analyse, des algorithmes métaheuristiques sont étudiés pour résoudre le problème. Nous montrons tout d'abord que un Greedy Local Search (GLS) et un recuit simulé (SA) peuvent trouver de meilleures solutions que les approches existantes implémentées dans le système UMTS, mais la multiplicité des optima locaux rend les algorithmes très instables. Un algorithme de recherche tabou (TS) incluant une recherche à voisinage variable (VNS) est aussi développé et comparé aux autres algorithmes (GLS et SA) et aux approches actuelles du système UMTS ; les résultats de la recherche tabou dépassent toutes les autres approches. Enfin les meilleures solutions trouvées par TS sont également comparées avec les solutions théoriques générées par le solveur MCKP. On constate que les meilleures solutions trouvées par TS sont égales ou très proches des solutions optimales théoriques. / The high throughputs supported by the multimedia multicast services (MBMS) and the limited radio resources result in strong requirement for efficient radio resource management (RRM) in UMTS 3G networks. This PhD thesis proposes to solve the MBMS RRM problem as a combinatorial optimization problem. The work starts with a formal modeling of the problem, named as the Flexible Radio Resource Management Model (F2R2M). An in-depth analysis of the problem complexity and the search landscape is done from the model. It is showed that, by relaxing the OVSF code constraints, the MBMS RRM problem can be approximated as a Multiple-Choice Knapsack Problem (MCKP). Such work allows us to compute the theoretical solution bounds by solving the approximated MCKP. Then the fitness landscape analysis shows that the search spaces are rough and reveal several local optimums. Based on the analysis, some metaheuristic algorithms are studied to solve the MBMS RRM problem. We first show that a Greedy Local Search (GLS) and a Simulated Annealing (SA) allow us to find better solutions than the existing approaches implemented in the UMTS system, however the results are instable due to the landscape roughness. Finally we have developed a Tabu Search (TS) mixed with a Variable Neighborhood Search (VNS) algorithm and we have compared it with GLS, SA and UMTS embedded algorithms. Not only the TS outperforms all the other approaches on several scenarios but also, by comparing it with the theoretical solution bounds generated by the MCKP solver, we observe that TS is equal or close to the theoretical optimal solutions.
17

Scalable cost-efficient placement and chaining of virtual network functions / Posicionamento e encadeamento escalável e baixo custo de funções virtualizados de rede

Luizelli, Marcelo Caggiani January 2017 (has links)
A Virtualização de Funções de Rede (NFV – Network Function Virtualization) é um novo conceito arquitetural que está remodelando a operação de funções de rede (e.g., firewall, gateways e proxies). O conceito principal de NFV consiste em desacoplar a lógica de funções de rede dos dispositivos de hardware especializados e, desta forma, permite a execução de imagens de software sobre hardware de prateleira (COTS – Commercial Off-The-Shelf). NFV tem o potencial para tornar a operação das funções de rede mais flexíveis e econômicas, primordiais em ambientes onde o número de funções implantadas pode chegar facilmente à ordem de centenas. Apesar da intensa atividade de pesquisa na área, o problema de posicionar e encadear funções de rede virtuais (VNF – Virtual Network Functions) de maneira escalável e com baixo custo ainda apresenta uma série de limitações. Mais especificamente, as estratégias existentes na literatura negligenciam o aspecto de encadeamento de VNFs (i.e., objetivam sobretudo o posicionamento), não escalam para o tamanho das infraestruturas NFV (i.e., milhares de nós com capacidade de computação) e, por último, baseiam a qualidade das soluções obtidas em custos operacionais não representativos. Nesta tese, aborda-se o posicionamento e o encadeamento de funções de rede virtualizadas (VNFPC – Virtual Network Function Placement and Chaining) como um problema de otimização no contexto intra- e inter-datacenter. Primeiro, formaliza-se o problema VNFPC e propõe-se um modelo de Programação Linear Inteira (ILP) para resolvêlo. O objetivo consiste em minimizar a alocação de recursos, ao mesmo tempo que atende aos requisitos e restrições de fluxo de rede. Segundo, aborda-se a escalabilidade do problema VNFPC para resolver grandes instâncias do problema (i.e., milhares de nós NFV). Propõe-se um um algoritmo heurístico baseado em fix-and-optimize que incorpora a meta-heurística Variable Neighborhood Search (VNS) para explorar eficientemente o espaço de solução do problema VNFPC. Terceiro, avalia-se as limitações de desempenho e os custos operacionais de estratégias típicas de aprovisionamento ambientes reais de NFV. Com base nos resultados empíricos coletados, propõe-se um modelo analítico que estima com alta precisão os custos operacionais para requisitos de VNFs arbitrários. Quarto, desenvolve-se um mecanismo para a implantação de encadeamentos de VNFs no contexto intra-datacenter. O algoritmo proposto (OCM – Operational Cost Minimization) baseia-se em uma extensão da redução bem conhecida do problema de emparelhamento ponderado (i.e., weighted perfect matching problem) para o problema de fluxo de custo mínimo (i.e., min-cost flow problem) e considera o desempenho das VNFs (e.g., requisitos de CPU), bem como os custos operacionais estimados. Os resultados alcaçados mostram que o modelo ILP proposto para o problema VNFPC reduz em até 25% nos atrasos fim-a-fim (em comparação com os encadeamentos observados nas infra-estruturas tradicionais) com um excesso de provisionamento de recursos aceitável – limitado a 4%. Além disso, os resultados evidenciam que a heurística proposta (baseada em fix-and-optimize) é capaz de encontrar soluções factíveis de alta qualidade de forma eficiente, mesmo em cenários com milhares de VNFs. Além disso, provê-se um melhor entendimento sobre as métricas de desempenho de rede (e.g., vazão, consumo de CPU e capacidade de processamento de pacotes) para as estratégias típicas de implantação de VNFs adotadas infraestruturas NFV. Por último, o algoritmo proposto no contexto intra-datacenter (i.e. OCM) reduz significativamente os custos operacionais quando comparado aos mecanismos de posicionamento típicos uti / Network Function Virtualization (NFV) is a novel concept that is reshaping the middlebox arena, shifting network functions (e.g. firewall, gateways, proxies) from specialized hardware appliances to software images running on commodity hardware. This concept has potential to make network function provision and operation more flexible and cost-effective, paramount in a world where deployed middleboxes may easily reach the order of hundreds. Despite recent research activity in the field, little has been done towards scalable and cost-efficient placement & chaining of virtual network functions (VNFs) – a key feature for the effective success of NFV. More specifically, existing strategies have neglected the chaining aspect of NFV (focusing on efficient placement only), failed to scale to hundreds of network functions and relied on unrealistic operational costs. In this thesis, we approach VNF placement and chaining as an optimization problem in the context of Inter- and Intra-datacenter. First, we formalize the Virtual Network Function Placement and Chaining (VNFPC) problem and propose an Integer Linear Programming (ILP) model to solve it. The goal is to minimize required resource allocation, while meeting network flow requirements and constraints. Then, we address scalability of VNFPC problem to solve large instances (i.e., thousands of NFV nodes) by proposing a fixand- optimize-based heuristic algorithm for tackling it. Our algorithm incorporates a Variable Neighborhood Search (VNS) meta-heuristic, for efficiently exploring the placement and chaining solution space. Further, we assess the performance limitations of typical NFV-based deployments and the incurred operational costs of commodity servers and propose an analytical model that accurately predict the operational costs for arbitrary service chain requirements. Then, we develop a general service chain intra-datacenter deployment mechanism (named OCM – Operational Cost Minimization) that considers both the actual performance of the service chains (e.g., CPU requirements) as well as the operational incurred cost. Our novel algorithm is based on an extension of the well-known reduction from weighted matching to min-cost flow problem. Finally, we tackle the problem of monitoring service chains in NFV-based environments. For that, we introduce the DNM (Distributed Network Monitoring) problem and propose an optimization model to solve it. DNM allows service chain segments to be independently monitored, which allows specialized network monitoring requirements to be met in a efficient and coordinated way. Results show that the proposed ILP model for the VNFPC problem leads to a reduction of up to 25% in end-to-end delays (in comparison to chainings observed in traditional infrastructures) and an acceptable resource over-provisioning limited to 4%. Also, we provide strong evidences that our fix-and-optimize based heuristic is able to find feasible, high-quality solutions efficiently, even in scenarios scaling to thousands of VNFs. Further, we provide indepth insights on network performance metrics (such as throughput, CPU utilization and packet processing) and its current limitations while considering typical deployment strategies. Our OCM algorithm reduces significantly operational costs when compared to the de-facto standard placement mechanisms used in Cloud systems. Last, our DNM model allows finer grained network monitoring with limited overheads. By coordinating the placement of monitoring sinks and the forwarding of network monitoring traffic, DNM can reduce the number of monitoring sinks and the network resource consumption (54% lower than a traditional method).
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Scalable cost-efficient placement and chaining of virtual network functions / Posicionamento e encadeamento escalável e baixo custo de funções virtualizados de rede

Luizelli, Marcelo Caggiani January 2017 (has links)
A Virtualização de Funções de Rede (NFV – Network Function Virtualization) é um novo conceito arquitetural que está remodelando a operação de funções de rede (e.g., firewall, gateways e proxies). O conceito principal de NFV consiste em desacoplar a lógica de funções de rede dos dispositivos de hardware especializados e, desta forma, permite a execução de imagens de software sobre hardware de prateleira (COTS – Commercial Off-The-Shelf). NFV tem o potencial para tornar a operação das funções de rede mais flexíveis e econômicas, primordiais em ambientes onde o número de funções implantadas pode chegar facilmente à ordem de centenas. Apesar da intensa atividade de pesquisa na área, o problema de posicionar e encadear funções de rede virtuais (VNF – Virtual Network Functions) de maneira escalável e com baixo custo ainda apresenta uma série de limitações. Mais especificamente, as estratégias existentes na literatura negligenciam o aspecto de encadeamento de VNFs (i.e., objetivam sobretudo o posicionamento), não escalam para o tamanho das infraestruturas NFV (i.e., milhares de nós com capacidade de computação) e, por último, baseiam a qualidade das soluções obtidas em custos operacionais não representativos. Nesta tese, aborda-se o posicionamento e o encadeamento de funções de rede virtualizadas (VNFPC – Virtual Network Function Placement and Chaining) como um problema de otimização no contexto intra- e inter-datacenter. Primeiro, formaliza-se o problema VNFPC e propõe-se um modelo de Programação Linear Inteira (ILP) para resolvêlo. O objetivo consiste em minimizar a alocação de recursos, ao mesmo tempo que atende aos requisitos e restrições de fluxo de rede. Segundo, aborda-se a escalabilidade do problema VNFPC para resolver grandes instâncias do problema (i.e., milhares de nós NFV). Propõe-se um um algoritmo heurístico baseado em fix-and-optimize que incorpora a meta-heurística Variable Neighborhood Search (VNS) para explorar eficientemente o espaço de solução do problema VNFPC. Terceiro, avalia-se as limitações de desempenho e os custos operacionais de estratégias típicas de aprovisionamento ambientes reais de NFV. Com base nos resultados empíricos coletados, propõe-se um modelo analítico que estima com alta precisão os custos operacionais para requisitos de VNFs arbitrários. Quarto, desenvolve-se um mecanismo para a implantação de encadeamentos de VNFs no contexto intra-datacenter. O algoritmo proposto (OCM – Operational Cost Minimization) baseia-se em uma extensão da redução bem conhecida do problema de emparelhamento ponderado (i.e., weighted perfect matching problem) para o problema de fluxo de custo mínimo (i.e., min-cost flow problem) e considera o desempenho das VNFs (e.g., requisitos de CPU), bem como os custos operacionais estimados. Os resultados alcaçados mostram que o modelo ILP proposto para o problema VNFPC reduz em até 25% nos atrasos fim-a-fim (em comparação com os encadeamentos observados nas infra-estruturas tradicionais) com um excesso de provisionamento de recursos aceitável – limitado a 4%. Além disso, os resultados evidenciam que a heurística proposta (baseada em fix-and-optimize) é capaz de encontrar soluções factíveis de alta qualidade de forma eficiente, mesmo em cenários com milhares de VNFs. Além disso, provê-se um melhor entendimento sobre as métricas de desempenho de rede (e.g., vazão, consumo de CPU e capacidade de processamento de pacotes) para as estratégias típicas de implantação de VNFs adotadas infraestruturas NFV. Por último, o algoritmo proposto no contexto intra-datacenter (i.e. OCM) reduz significativamente os custos operacionais quando comparado aos mecanismos de posicionamento típicos uti / Network Function Virtualization (NFV) is a novel concept that is reshaping the middlebox arena, shifting network functions (e.g. firewall, gateways, proxies) from specialized hardware appliances to software images running on commodity hardware. This concept has potential to make network function provision and operation more flexible and cost-effective, paramount in a world where deployed middleboxes may easily reach the order of hundreds. Despite recent research activity in the field, little has been done towards scalable and cost-efficient placement & chaining of virtual network functions (VNFs) – a key feature for the effective success of NFV. More specifically, existing strategies have neglected the chaining aspect of NFV (focusing on efficient placement only), failed to scale to hundreds of network functions and relied on unrealistic operational costs. In this thesis, we approach VNF placement and chaining as an optimization problem in the context of Inter- and Intra-datacenter. First, we formalize the Virtual Network Function Placement and Chaining (VNFPC) problem and propose an Integer Linear Programming (ILP) model to solve it. The goal is to minimize required resource allocation, while meeting network flow requirements and constraints. Then, we address scalability of VNFPC problem to solve large instances (i.e., thousands of NFV nodes) by proposing a fixand- optimize-based heuristic algorithm for tackling it. Our algorithm incorporates a Variable Neighborhood Search (VNS) meta-heuristic, for efficiently exploring the placement and chaining solution space. Further, we assess the performance limitations of typical NFV-based deployments and the incurred operational costs of commodity servers and propose an analytical model that accurately predict the operational costs for arbitrary service chain requirements. Then, we develop a general service chain intra-datacenter deployment mechanism (named OCM – Operational Cost Minimization) that considers both the actual performance of the service chains (e.g., CPU requirements) as well as the operational incurred cost. Our novel algorithm is based on an extension of the well-known reduction from weighted matching to min-cost flow problem. Finally, we tackle the problem of monitoring service chains in NFV-based environments. For that, we introduce the DNM (Distributed Network Monitoring) problem and propose an optimization model to solve it. DNM allows service chain segments to be independently monitored, which allows specialized network monitoring requirements to be met in a efficient and coordinated way. Results show that the proposed ILP model for the VNFPC problem leads to a reduction of up to 25% in end-to-end delays (in comparison to chainings observed in traditional infrastructures) and an acceptable resource over-provisioning limited to 4%. Also, we provide strong evidences that our fix-and-optimize based heuristic is able to find feasible, high-quality solutions efficiently, even in scenarios scaling to thousands of VNFs. Further, we provide indepth insights on network performance metrics (such as throughput, CPU utilization and packet processing) and its current limitations while considering typical deployment strategies. Our OCM algorithm reduces significantly operational costs when compared to the de-facto standard placement mechanisms used in Cloud systems. Last, our DNM model allows finer grained network monitoring with limited overheads. By coordinating the placement of monitoring sinks and the forwarding of network monitoring traffic, DNM can reduce the number of monitoring sinks and the network resource consumption (54% lower than a traditional method).
19

Meta-heurísticas baseadas em busca em vizinhança variável aplicadas a problemas de operação de transportes. / Metaheuristic based on variable neighbourhood search applied to operation transport problems.

Jorge Von Atzingen dos Reis 30 September 2013 (has links)
Esta pesquisa trata da aplicação de meta-heurísticas baseadas em busca em vizinhança variável em problemas de operação de transportes. Desta forma, buscou-se encontrar problemas complexos durante a operação de sistemas de transportes, nas grandes cidades, que possam ser resolvidos com a aplicação de meta-heurística baseada em busca em vizinhança variável. Este trabalho aborda dois diferentes problemas de planejamento e operação de transportes. O primeiro problema abordado neste trabalho é o Problema de Programação da Tabela de Horários, de Veículos e de Tripulantes de Ônibus, no qual as viagens que comporão a tabela de horários, os veículos que executarão as viagens e as tripulações que operarão os veículos são alocadas simultaneamente e de maneira integrada. O segundo problema a ser abordado é o problema de distribuição física, o qual envolve o agrupamento e a alocação de entregas a uma frota de veículos visando minimizar o frete total. Uma abordagem para a modelagem matemática deste problema é modelar como um problema de bin-packing, com bins de tamanho variável unidimensional (do inglês Variable Sized Bin-Packing Problem - VSBPP), ou seja, uma generalização do tradicional problema de bin-packing no qual bins (veículos) de diferentes capacidades e custos estão disponíveis para a alocação de um conjunto de objetos (cargas), de modo que o custo total dos bins (veículos) utilizados seja mínimo. A outra abordagem proposta para o problema de distribuição física é modelar o problema como um problema de bin-packing, com bins de tamanho variável bidimensional (do inglês Bidimensional Variable Sized Bin-Packing Problem BiD-VSBPP). Assim sendo, trata-se de uma expansão do problema de bin-packing com bins de tamanho variável unidimensional (VSBPP), no qual bins (veículos) de diferentes capacidades (capacidade volumétrica e capacidade de carga) e custos estão disponíveis para a alocação de um conjunto de objetos (cargas), os quais possuem as dimensões peso e volume, de modo que o custo total dos bins (veículos) utilizados seja mínimo. Durante a realização deste trabalho, foi desenvolvido um programa computacional em C++, o qual implementa a meta-heurística Busca em Vizinhança Variável (VNS) e duas meta-heurísticas baseadas em VNS. São apresentados resultados de experimentos computacionais com dados reais e dados benchmarking. Os resultados obtidos comprovam a eficácia das meta-heurísticas propostas. / This work approaches variable neighborhood search meta-heuristic applicate on transport operation problems. This way, we sought find complex transport operation problems in large cities that can be solved with the variable neighborhood search meta-heuristic application. This work approaches two different transport planning and operation problems. The first problem approached in this paper is the Bus Timetable Vehicle Crew Scheduling Problem, in which timetabling, bus and crew schedules are simultaneously determined in an integrated approach. The second problem to be approached is the physical distribution problem which comprises grouping and assigning deliveries to a heterogeneous fleet of vehicles aiming to minimize the total freight cost. The problem can be mathematical modeled as one-dimensional Variable Sized Bin-Packing Problem (VSBPP), a generalization of the traditional bin-packing problem, in which bins (vehicles) with different sizes and costs are available for the assignment of the objects (deliveries) such that the total cost of the used bins (vehicles) is minimized. Another proposed approach to the problem of physical distribution is model as two dimensional Variable Sized Bin-Packing Problem (BiD-VSBPP). Therefore, it is an expansion of the bin-packing problem with bins variable-length-dimensional (VSBPP), in which bins (vehicle) of different capacity (capacity and load carrying capacity) and costs are available for allocation a set of objects (loads), which have the dimensions weight and volume, so that minimized the total cost of bins (vehicle). In this work, was developed a C++ software implemented, which was implemented a meta-heuristic Variable Neighborhood Search (VNS) and two others meta-heuristics based on VNS. Computational results for real-world problems and benchmarking problems are presented, showing the effectiveness of these proposed meta-heuristics.
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Une matheuristique unifiée pour résoudre des problèmes de tournées de véhicules riches / Unified matheuristic for solving rich vehicle routing problems

Lahyani, Rahma 13 June 2014 (has links)
L’objectif de cette thèse est de développer un cadre méthodologique pour les problèmes de tournées de véhicules riches (RVRPs). Nous présentons d’abord une taxonomie et une définition élaborée des RVRPs basée sur une analyse typologique réalisée en fonction de deux critères discriminatoires. Dans cette thèse, nous nous intéressons à la résolution du problème de tournées de véhicules multi-dépôt multi-compartiment multi-produits avec fenêtres de temps (MDMCMCm-VRPTW). Nous proposons une heuristique de génération de colonnes unifiée qui inclut une matheuristique de type VNS. La matheuristique combine plusieurs heuristiques de routage de type destruction et insertion ainsi que des procédures efficaces de contrôle de réalisabilité des contraintes afin de résoudre le MDMCMCm-VRPTW pour un seul véhicule. Deux voisinages de chargement, basés sur la résolution de programmes mathématiques sont proposées. Des études expérimentales approfondies sont conduites sur un ensemble de 191 instances pour des VRPs moins complexes. Les expérimentations valident la compétitivité de la matheuristique unifiée. Une analyse de sensibilité révèle l’importance de certains choix algorithmiques et des voisinages de chargement pour parvenir à des solutions de très bonne qualité. La matheuristique basée sur la méthode de VNS est intégrée dans l’heuristique de génération de colonnes pour résoudre le MDMCMCm-VRPTW. Nous proposons une méthode exacte de post-traitement capable d’optimiser l’affectation des clients aux tournées de véhicules. Enfin, nous résolvons un RVRP qui survient dans le processus de collecte de l’huile d’olive en Tunisie à l’aide d’un algorithme exact de type branch-and-cut / The purpose of this thesis is to develop a solution framework for Rich Vehicle Routing Problems (RVRPs). We first provide a comprehensive survey of the RVRP literature as well as a taxonomy. Selected papers addressing various variants are classified according to the proposed taxonomy. A cluster analysis based on two discriminating criteria is performed and leads to define RVRPs. In this thesis we are interested in solving a multi-depot multi-compartment multi-commodity vehicle routing problem with time windows (MDMCMCm-VRPTW). We propose a unified column generation heuristic cooperating with a variable neighborhood search (VNS) matheuristic. The VNS combines several removal and insertion routing heuristics as well as computationally efficient constraint checking. Two loading neighborhoods based on the solution of mathematical programs are proposed to intensify the search. On a set of 191 instances of less complex routing problems, the unified matheuristic turns to be competitive. A sensitivity analysis, performed on more complex generated instances reveals the importance of some algorithmic features and of loading neighborhoods for reaching high quality solutions. The VNS based matheuristic is embedded in a column generation heuristic to solve the MDMCMCm-VRPTW. We propose an exact post-processing method to optimize the assignment ofcustomers to vehicle routes. Last, we introduce, model and solve to optimality a RVRP arising in the olive oil collection process in Tunisia. We propose an exact branch-and-cut algorithm to solve the problem. We evaluate the performance of the algorithm on real data sets under different transportation scenarios

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