6 research outputs found

    Resource Management and Pricing in Networks

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    Resource management is important for network design and deployment. Resource management and allocation have been studied under a wide variety of scenarios --- routing in wired networks, scheduling in cellular networks, multiplexing, switching, and channel access in opportunistic networks are but a few examples. In this dissertation, we revisit resource management in the context of routing and scheduling in multihop wireless networks and pricing in single resource systems. The first issue addressed is of delays in multihop wireless networks. The resource under contention is capacity which is allocated by a joint routing and scheduling algorithm. Delay in wireless networks is a key issue gaining interest with the growth of interactive applications and proliferation of wireless networks. We start with an investigation of the back-pressure algorithm (BPA), an algorithm that activates the schedule with the largest sum of link weights in a timeslot. Though the BPA is throughput-optimal, it has poor end-to-end delays. Our investigation identifies poor routing decisions at low loads as one cause for it. We improve the delay performance of max-weight algorithms by proposing a general framework for routing and scheduling algorithms that allow directing packets towards the sink node dynamically. For a stationary environment, we explicitly formulate delay minimization as a static problem while maintaining stability. We see similar improved delay performance with the advantage of reduced per time-slot complexity. Next, the issue of pricing for flow based models is studied. The increasing popularity of cloud computing and the ease of commerce over the Internet is making pricing a key issue requiring greater attention. Although pricing has been extensively studied in the context of maximizing revenue and fairness, we take a different perspective and investigate pricing with predictability. Prior work has studied resource allocations that link insensitivity and predictability. In this dissertation, we present a detailed analysis of pricing under insensitive allocations. We study three common pricing models --- fixed rate pricing, Vickrey-Clarke-Groves (VCG) auctions, and congestion-based pricing, and provide the expected operator revenue and user payments under them. A pre-payment scheme is also proposed where users pay on arrival a fee for their estimated service costs. Such a mechanism is shown to have lower variability in payments under fixed rate pricing and VCG auctions while generating the same long-term revenue as in a post-payment scheme, where users pay the exact charge accrued during their sojourn. Our formulation and techniques further the understanding of pricing mechanisms and decision-making for the operator

    Modelling users in networks with path choice: four studies in telecommunications and transit

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    Networks of interacting users arise in many important modelling applications. Commuters interact with each other and form traffic jams during peak-time. Network protocols are users in a communication network that control sending rate and server choice. When protocols send with too high rates, network links get overloaded resulting in lost data and high delays. Although these two example users seem very different, they are similar on a conceptual modelling level. Accurate user models are essential to study complex interactions in networks. The behaviour of a user with access to different paths in a network can be modelled as an optimisation problem. Users who choose paths with the highest utility are common in many different application areas, for example road traffic, Internet protocol modelling, and general societal networks, i.e. networks of humans in everyday life. Optimisation-based user models are also attractive from the perspective of a modeller since they often allow the derivation of insights about the behaviour of the entire system by only describing a user model. The aim of this thesis is to show, in four practical studies from telecommunications and transit networks, where optimisation-based models have limitations when modelling users with path choice. We study users who have access to a limited number of paths in large scale data centers and investigate how many paths per user are realistically needed in order to get high throughput in the network. In multimedia streaming, we study a protocol that streams data on multiple paths and path properties matter. We also investigate complex energy models for data interfaces on mobile phones and evaluate how to switch interfaces to save energy. Finally, we analyse a long-term data set from 20,000 transit commuters and give insights on how they change their travel behaviour in response to incentives and targeted offers. We use tools from optimisation, simulation, and statistics to evaluate the four studies and point out problems we faced when modelling and implementing the system. The findings of this thesis indicate where user models need to be extended in order to be of practical use. The results can serve as a guide towards better user models for future modelling applications

    Exploration of alternative frameworks for transportation infrastructure strategy development

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2010.Cataloged from PDF version of thesis.Includes bibliographical references.This thesis introduces the notion of a strategy development framework for transportation infrastructure systems. A strategy development framework has several dimensions: the organizations that own.infrastructure, the ownership structure employed, the type and quantity of revenues generated, the revenue allocation methods for re-investing in the infrastructure, the degree of integration across transportation modes and other sectors, and the geographic scales controlled. We analyze the behavior of a range of alternative frameworks through a combined quantitative-qualitative approach, using Portugal's highway transportation system as the context. Drawing on strategy literature from the management field, we begin by defining and characterizing a range of alternative strategy development frameworks for transportation infrastructure systems. Next, we analyze these frameworks quantitatively using an agent-based model which simulates the evolution of Portugal's intercity highway network over time and space. By varying the frameworks' dimensions (e.g., type of revenue, revenue allocation method, geographic scale of control), we observe differences in the resulting investment decisions for the network. We evaluate the performance of these investment decisions according to a range of metrics in order to determine which frameworks lead to desirable outcomes. The simulation, however, cannot fully capture the relationship between a framework and investment outcomes for the highway system, so we complement the model with a qualitative analysis which combines empirical cases and predicted stakeholder dynamics. The integrated quantitative-qualitative evaluation allows us to explain a wider range of trade-offs associated with each alternative framework. The contributions of this research are threefold: (1) we offer the notion of strategy development, which allows for recognition and inclusion of emergent outcomes, as an alternative to the narrower concept of transportation planning; (2) we determine the influence of advanced transportation technologies (typically studied for their operational benefits) on strategy development; and (3) we explore the consequences of fundamental changes to the strategy development framework, notably along the dimension of geographic scale. While our theory and methods are applied to the case of Portugal's highway system-and we strive to produce results of value to that nation-we believe they can be profitably applied in other transportation contexts as well.by Travis P. Dunn.Ph.D

    Um modelo de otimização para planejamento dinâmico de voo para grupos de drones por meio de sistema multiagente e leilões recursivos

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    Orientador: Eduardo TodtTese (doutorado) - Universidade Federal do Paraná, Setor de Ciências Exatas, Programa de Pós-Graduação em Informática. Defesa : Curitiba, 03/07/2020Inclui referênciasÁrea de concentração: Ciência da ComputaçãoResumo: Este trabalho apresenta um modelo aplicado de cooperacao para otimizar voos de veiculos aereos nao tripulados do tipo quadricoptero, tambem conhecidos como Drones, com aplicacao na agricultura de precisao. O modelo utiliza Sistema Multiagente para permitir a abertura, que e a propriedade de inserir e retirar elementos do modelo a qualquer momento. Para garantir a dinamicidade, que e a caracteristica que o modelo tem de se recuperar de eventos adversos ou falhas, agentes cognitivos com BDI foram utilizados. Para garantir a troca de mensagens independente da quantidade de elementos no modelo, foi utilizado o protocolo FIPA Contract-NET. Um algoritmo distribuido de otimizacao utilizando leiloes recursivos tambem foi desenvolvido, o qual visa otimizar o tempo de voo, assim como o uso da bateria dos Drones, sendo a bateria a grande limitacao destes e inibindo sua utilizacao na agricultura de precisao. Esse algoritmo foi testado em seu modelo original e, posteriormente, refinado a partir de heuristicas e metodologias visando diminuir o numero de leiloes recursivos, assim como o tempo de processamento, em comparacao ao modelo original. Este modelo, apos aplicacao das heuristicas e metodologias, foi testado. Em cenarios contendo multiplos Drones, o desempenho foi 30% superior ao algoritmo dinamico encontrado na literatura que tambem pode ser aplicado em ambientes dinamicos. Do ponto de vista de abertura e dinamicidade, o modelo foi testado no simulador MultiDrone Simulator, permitindo gerar novos planos de voo, mesmo com eventos adversos. Os resultados dos testes em simulacao realizados sustentam que o modelo proposto apresenta comportamento como esperado, mostrando-se como uma plataforma promissora de pesquisa para uso de Drones em cenarios da agricultura de precisao, uma vez que este modelo permite a utilizacao de multiplos Drones em ambientes dinamicos e abertos, garantindo a otimizacao do tempo de voo, o que garante economia da bateria dos Drones. Palavras-chave: Drones, Sistema Multiagente, BDI, Leilao RecursivoAbstract: This work presents an applied model of cooperation to optimize flights of unmanned aerial vehicles like quadcopters, also known as Drones, involved in precision agriculture. This model uses a Multiagent System to allow up the opening, which is the property of inserting and removing elements from the model at any time. To allow dynamism, which is the characteristic that the model has to recover from adverse events or failures, cognitive agents with BDI structure were used. To guarantee the exchange of messages in dynamic number of elements, the FIPA Contract-NET protocol were used. A distributed optimization algorithm using recursive auctions was also developed, which aims to optimize the number of points covered by Drones. This model aims to optimize the flight time, which directly reflects the optimization of the Drone's battery use. This is a great limitation of this kind of aerial vehicle and which inhibits its use in precision agriculture. This algorithm was tested as original proposed and, later, refined from heuristics and methodologies in order to decrease the number of auctions, as well as the processing time. This model, after applying the heuristics and methodologies, was tested, and in scenarios containing multiple Drones, the performance was 30 % higher than the dynamic algorithm found in the literature that can also be applied in dynamic environments. From the point of view of openness and dynamics, the model was tested in the MultiDrone Simulator, allowing to generate new flight plans, even with the simulated adverse events. The results of the simulation tests carried out maintain that the proposed model behaves as expected, showing itself as a promising research platform for the use of drones in precision agriculture scenarios, since this model allows the use of multiple Drones in environments dynamic and open, guaranteeing the flight optimization, which ensures battery saving for Drones. Keywords: Drones, Multiagent System, BDI, Recursive Auction
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