Alocação de recursos em redes ópticas elásticas baseadas em multiplexação por divisão espacial

Orientador: Nelson Luis Saldanha da FonsecaDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Tecnologias de redes ópticas baseadas em fibras mono-núcleo e mono-modo possuem limite de capacidade e não conseguem suprir a demanda crescente de largura de banda. Um forma de resolver esse problema se dá através do uso de multiplexação por divisão espacial (SDM - \textit{Space-Division Multiplexing}). A transmissão de dados em SDM ocorre através de múltiplos núcleos agrupados em um único filamento de fibra, ou utilizando múltiplos modos transversais suportados por um núcleo. A combinação da flexibilidade de redes ópticas elásticas (EON - \textit{Elastic Optical Networks}) e a alta capacidade do SDM é promissora para o futuro das redes ópticas. Na camada de enlace, quando uma nova solicitação para estabelecimento de conexão chega, é necessário fazer a reserva de recursos para realizar essa conexão. A determinação dos recursos a serem alocados é dada pela solução do problema de roteamento, alocação de núcleo e \textit{slots} (RCSA - \textit{Routing, Core and Spectrum Allocation}). Na alocação de recursos, algumas restrições devem ser respeitadas, tais como a contiguidade e continuidade dos \textit{slots} de frequência, e tolerância ao \textit{crosstalk} espacial. Estas restrições implicam em uma maior complexidade para a acomodação do tráfego das conexões. A virtualização de redes permite que redes virtuais compartilhem recursos físicos, simplificando o gerenciamento de recursos na camada óptica, oferecendo flexibilidade na alocação de recursos e segurança dos serviços. Um dos principais desafios da virtualização é configurar de forma eficiente as redes virtuais, que consiste na alocação de recursos físicos para acomodá-las. Esta tese propõe soluções para o problema do RCSA em redes SDM-EON. A primeira contribuição desta tese é um algoritmo que considera o equilíbrio entre eficiência energética e bloqueio de requisições. Propõe-se um algoritmo de agregação de tráfego em lote, capitalizando na flexibilidade temporal para satisfazer requisições com o objetivo de formar lotes de requisições, aumentando assim a probabilidade de serem atendidas as requisições em um outro momento. A segunda contribuição desta tese é direcionada para a solução do problema da fragmentação, que ocorre em cenários onde pequenos conjuntos de \textit{slots} disponíveis ficam espalhados no espectro, causando o bloqueio de novas requisição. Propõem-se um conjunto de algoritmos proativos e reativos. Os algoritmos proativos utilizam diferentes técnicas, tais como, múltiplos caminhos, priorização de núcleo e área, bem como métricas de avaliação da fragmentação na composição de caminhos. O algoritmo reativo utiliza aprendizagem de máquina para fazer um rearranjo espectral e aumentar a capacidade de prevenção da fragmentação no RCSA. A terceira contribuição desta tese é uma solução para aumentar a eficiência do compartilhamento de recursos em redes virtuais. Este problema consiste na configuração de enlaces e nós virtuais para caminhos e nós físicos, respectivamente. A solução proposta introduz uma arquitetura utilizando aprendizado de máquina, que age como um assistente no processo de configuração de redes virtuaisAbstract: Optical network technologies based on a single-core and single-mode fibers have a limited capacity and cannot provide enough resources to a constant increase of bandwidth demands. One approach to overcome this is the use of Space-Division Multiplexing (SDM) which relies on sending data through multiple cores embedded into a single strand of fiber or using multiple transverse modes supported by a core. The combination of the flexibility of Elastic Optical Networks (EONs) and the high capacity of SDM is a promising solution to cope with the bandwidth demands. At the network level, when a traffic request arrives, it needs to reserve network resources to establish it. One approach to accommodate traffic demand over optical networks is the Routing, Core and Spectrum Allocation (RCSA), in which end-to-end lightpaths are offered for each individual request. In these scenarios, during the allocation process, some constraints need to be respected, such as contiguity and continuity of slots (selected in the resource selection process), and spatial crosstalk. These constraints pose extra complexity to accommodate the requests for the lightpath establishment. As one of the possible solutions, network virtualization is capable of improving the efficiency of optical networks, by allowing virtual networks to share the resources of physical networks, simplifying the management of resource and providing flexibility in resource allocation. One of the main challenges of network virtualization is to configure a virtual network efficiently which comprises allocating physical resources to accommodate incoming virtual networks. This thesis proposes solutions to the RCSA problem and the virtual network configuration problem for SDM-EON networks. The first contribution of this thesis is an algorithm to promote an equilibrium between reduction of the network energy consumption and reduction of the blocking of requests. For this purpose, we introduce a traffic grooming algorithm using batches, which takes advantage of the deadline of each request to form batches, increasing the chances of the requests to be established at another time. The second contribution of this thesis is a set of algorithms using different techniques to handle the fragmentation problem, where a small portion of available slot sequences end up scattered in a fiber link, blocking future requests, called the fragmentation problem. For this purpose, we propose proactive and reactive algorithms. Proactive algorithms use different techniques, such as multipath routing, core, and area prioritization, and metrics to use in the route selection process. The reactive algorithm uses machine learning to rearrange the spectrum and tune the RCSA algorithm to prevent the fragmentation. The third contribution of this thesis proposes a solution to improve resource sharing in network virtualization. This problem consists in configuring virtual links and nodes to physical nodes and paths. For this purpose, we propose a learning assistant control loop to handle the virtual network configuration problemMestradoCiência da ComputaçãoMestra em Ciência da Computação131025/2017-1CNP

Enabling Technology in Optical Fiber Communications: From Device, System to Networking

This book explores the enabling technology in optical fiber communications. It focuses on the state-of-the-art advances from fundamental theories, devices, and subsystems to networking applications as well as future perspectives of optical fiber communications. The topics cover include integrated photonics, fiber optics, fiber and free-space optical communications, and optical networking

Systematic Approaches for Telemedicine and Data Coordination for COVID-19 in Baja California, Mexico

Conference proceedings info: ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologies Raleigh, HI, United States, March 24-26, 2023 Pages 529-542We provide a model for systematic implementation of telemedicine within a large evaluation center for COVID-19 in the area of Baja California, Mexico. Our model is based on human-centric design factors and cross disciplinary collaborations for scalable data-driven enablement of smartphone, cellular, and video Teleconsul-tation technologies to link hospitals, clinics, and emergency medical services for point-of-care assessments of COVID testing, and for subsequent treatment and quar-antine decisions. A multidisciplinary team was rapidly created, in cooperation with different institutions, including: the Autonomous University of Baja California, the Ministry of Health, the Command, Communication and Computer Control Center of the Ministry of the State of Baja California (C4), Colleges of Medicine, and the College of Psychologists. Our objective is to provide information to the public and to evaluate COVID-19 in real time and to track, regional, municipal, and state-wide data in real time that informs supply chains and resource allocation with the anticipation of a surge in COVID-19 cases. RESUMEN Proporcionamos un modelo para la implementación sistemática de la telemedicina dentro de un gran centro de evaluación de COVID-19 en el área de Baja California, México. Nuestro modelo se basa en factores de diseño centrados en el ser humano y colaboraciones interdisciplinarias para la habilitación escalable basada en datos de tecnologías de teleconsulta de teléfonos inteligentes, celulares y video para vincular hospitales, clínicas y servicios médicos de emergencia para evaluaciones de COVID en el punto de atención. pruebas, y para el tratamiento posterior y decisiones de cuarentena. Rápidamente se creó un equipo multidisciplinario, en cooperación con diferentes instituciones, entre ellas: la Universidad Autónoma de Baja California, la Secretaría de Salud, el Centro de Comando, Comunicaciones y Control Informático. de la Secretaría del Estado de Baja California (C4), Facultades de Medicina y Colegio de Psicólogos. Nuestro objetivo es proporcionar información al público y evaluar COVID-19 en tiempo real y rastrear datos regionales, municipales y estatales en tiempo real que informan las cadenas de suministro y la asignación de recursos con la anticipación de un aumento de COVID-19. 19 casos.ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologieshttps://doi.org/10.1007/978-981-99-3236-

Bioinspired metaheuristic algorithms for global optimization

This paper presents concise comparison study of newly developed bioinspired algorithms for global optimization problems. Three different metaheuristic techniques, namely Accelerated Particle Swarm Optimization (APSO), Firefly Algorithm (FA), and Grey Wolf Optimizer (GWO) are investigated and implemented in Matlab environment. These methods are compared on four unimodal and multimodal nonlinear functions in order to find global optimum values. Computational results indicate that GWO outperforms other intelligent techniques, and that all aforementioned algorithms can be successfully used for optimization of continuous functions

Experimental Evaluation of Growing and Pruning Hyper Basis Function Neural Networks Trained with Extended Information Filter

In this paper we test Extended Information Filter (EIF) for sequential training of Hyper Basis Function Neural Networks with growing and pruning ability (HBF-GP). The HBF neuron allows different scaling of input dimensions to provide better generalization property when dealing with complex nonlinear problems in engineering practice. The main intuition behind HBF is in generalization of Gaussian type of neuron that applies Mahalanobis-like distance as a distance metrics between input training sample and prototype vector. We exploit concept of neuron’s significance and allow growing and pruning of HBF neurons during sequential learning process. From engineer’s perspective, EIF is attractive for training of neural networks because it allows a designer to have scarce initial knowledge of the system/problem. Extensive experimental study shows that HBF neural network trained with EIF achieves same prediction error and compactness of network topology when compared to EKF, but without the need to know initial state uncertainty, which is its main advantage over EKF

Federal Register

Daily publication of the U.S. Office of the Federal Register contains rules and regulations, proposed legislation and rule changes, and other notices, including "Presidential proclamations and Executive Orders, Federal agency documents having general applicability and legal effect, documents required to be published by act of Congress, and other Federal agency documents of public interest" (p. ii). Table of Contents starts on page iii

Federal Register

Daily publication of the U.S. Office of the Federal Register contains rules and regulations, proposed legislation and rule changes, and other notices, including "Presidential proclamations and Executive Orders, Federal agency documents having general applicability and legal effect, documents required to be published by act of Congress, and other Federal agency documents of public interest" (p. ii). Table of Contents starts on page iii