Multi-Period Planning With Actual Physical and Traffic Conditions

Soumplis, Polyzois; Christodoulopoulos, K.; Quagliotti, Marco; Pagano, A.; Varvarigos, Emmanouel

doi:10.1364/jocn.10.00a144

Cited by 27 publications

(28 citation statements)

References 17 publications

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“…Differently of the others approaches based on intelligent systems [14], it is not necessary the training phase and the proposed scheme can be performed in near-real time. In addition, the power budget is determinate in the planning stage of the network and margins are included [2], [4] and the proposed scheme will act during the regular operation of the EON. For the proposed scheme it is considered that the lightpaths were previously established from the resource allocation algorithms associated with route, modulation, bandwidth and spectrum.…”

Section: Proposed Schemementioning

confidence: 99%

“…Currently, the technological maturity of devices, equipment and protocols provides the use of dynamical flexible grid-rate elastic optical network (EON). In the EONs, the lightpaths with adjustable bandwidth, modulation level and spectrum assignment can be established according to actual traffic demands and quality of service (QoS) requirements [1], [2]. In addition, the quality of transmission (QoT) of each lightpath is evaluated previously to resources allocation purpose, as well as to obtain reliable optical connectivity [2], [3].…”

Section: Introductionmentioning

confidence: 99%

“…In the EONs, the lightpaths with adjustable bandwidth, modulation level and spectrum assignment can be established according to actual traffic demands and quality of service (QoS) requirements [1], [2]. In addition, the quality of transmission (QoT) of each lightpath is evaluated previously to resources allocation purpose, as well as to obtain reliable optical connectivity [2], [3]. The best knowledge of the QoT is needed in the design and operation phases, owing to the margin has to be added in the network when the QoT is not well established [4].…”

Section: Introductionmentioning

confidence: 99%

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Heuristic Chaotic Hurricane-Aided Efficient Power Assignment for Elastic Optical Network

Santos

Abrão

2020

IEEE Access

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In this paper, we propose a dynamical power allocation (PA) procedure for elastic optical networks (EONs) based on the evolutionary hurricane search optimization (HSO) algorithm with a chaotic logistic map diversification strategy with the purpose of improving the capability to escape from local optima, namely PA-CHSO. The aiming is the dynamical control of the transmitted optical powers according to the variations of each link state due to traffic fluctuations, channel impairments, as well as other channel-power coupling effects. Such realistic EON scenarios are affected mainly by the channel estimation inaccuracy, channel ageing and power fluctuations. The link state is based on the channel estimation and quality of transmission (QoT) parameters obtained from the optical performance monitors (OPMs). Numerical results have demonstrated the effectiveness of the PA-CHSO to dynamically mitigate the power penalty under real measurement conditions with uncertainties and noise, as well as when perturbations in the optical transmit powers are considered. INDEX TERMS Adaptive power control algorithm, optical networks, hurricane algorithm, chaotic map, elastic optical networks.

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Section: Proposed Schemementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Heuristic Chaotic Hurricane-Aided Efficient Power Assignment for Elastic Optical Network

Santos

Abrão

2020

IEEE Access

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“…[Velasco et al 2016] considerou o planejamento da expansão da capacidade da rede em regime multiperíodo, para previsões de demanda de tráfego médio crescente com ajuda de alguns modelos matemáticos. [Soumplis et al 2017] apresentou um algoritmo para fazer o planejamento de redes em condições de tráfego incremental e mostrou até 36% de melhoras em gastos. [Iyer and Singh 2018] propôs formulações de ILP para minimizar o custo de operação em redes multicamadas, considerando tráfego incremental.…”

Section: Tráfego Incrementalunclassified

Análise Sobre Redes Ópticas com Heurísticas de Roteamento, Modulação e Alocação de Espectro para Tráfego Incremental

Mesquita

Assis

2019

Anais Do XXXVII Simpósio Brasileiro De Redes De Computadores E Sistemas Distribuídos (SBRC 2019)

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Os avanços na tecnologia de transmissão óptica de dados permitiram o grande crescimento da internet e de serviços exigentes em largura de banda. O surgimento das redes baseadas em Multiplexação por divisão de frequência ortogonal (OFDM) abriram a possibilidade de se aumentar a eficiência espectral de uma rede através da resolução do problema de roteamento e alocação de espectro (RSA). Neste trabalho, foram implementadas duas heurísticas de RSA que consideram diferentes formatos de modulação disponíveis (RMSA). Simulações foram feitas para diversas redes, usando as heurísticas, em condições de tráfego incremental. Os resultados mostraram que a heurística de alocação por balanceamento de carga (BMLM) tendeu a apresentar menor taxa de bloqueio nos períodos iniciais, quando havia apenas um formato de modulação disponível, mas apresentou maior taxa de bloqueio, a longo prazo, relativa à heurística por alocação de caminho mais curto (SPMLM). Quando mais formatos de modulação estavam disponíveis, o BMLM apresentou pior desempenho na maioria dos casos, mas conseguiu melhores resultados em algumas redes.

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“…Margined formulas have also been used to reduce computational load, but lead to network over-dimensioning [2]. Recent studies aim at reducing these margins by proposing schemes based on active monitoring [3], considering actual physical and traffic conditions in multi-period scenarios [4] or using monitored physical parameters in a learning process [5]. In fact, the adoption of artificial intelligence techniques, and in particular Machine Learning (ML), to estimate lightpath QoT is a very promising trend, as they may provide fast and accurate estimates, and may be able to adapt to changing conditions [6], [7], [8].…”

Section: Introductionmentioning

confidence: 99%

Supervised Machine Learning Techniques for Quality of Transmission Assessment in Optical Networks

Mata

Miguel

Durán

et al. 2018

2018 20th International Conference on Transparent Optical Networks (ICTON)

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We propose and compare a number of machine learning models to classify unestablished lightpaths into high or low quality of transmission (QoT) categories in impairment-aware wavelength-routed optical networks. The performance of these models is evaluated in long haul communication networks and compared to previous proposals. Results show that, especially random forests and bagging trees approaches, significantly reduce the required computing time to classify the QoT of a given lightpath, while accuracy remains around 99.9%.

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Multi-Period Planning With Actual Physical and Traffic Conditions

Cited by 27 publications

References 17 publications

Heuristic Chaotic Hurricane-Aided Efficient Power Assignment for Elastic Optical Network

Heuristic Chaotic Hurricane-Aided Efficient Power Assignment for Elastic Optical Network

Análise Sobre Redes Ópticas com Heurísticas de Roteamento, Modulação e Alocação de Espectro para Tráfego Incremental

Supervised Machine Learning Techniques for Quality of Transmission Assessment in Optical Networks

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