NeTS: Small: Modeling and Alleviating Physical Impairments in Translucent EONs
NeTS: Small: Modeling and Alleviating Physical Impairments in Translucent EONs
批准号:
1718130
负责人:
Maite Brandt-Pearce
金额:
$35.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-09-01 至 2022-08-31
中文摘要
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英文摘要
Society has shown an endless appetite for new data-rich applications running over the Internet, which depends on fiber-optic networks to carry its traffic. Elastic optical networks (EONs) are widely seen as the logical evolution of current large-scale fiber-optic core transport networks due to their flexibility and ability to support growing capacity demands. They can also deploy advanced signal processing techniques to balance the requirements of high resource efficiency and high signal quality. The goal of this proposed work is to design long-haul EONs and invent algorithms that wisely employ its system resources, including the optical spectrum as well as physical network equipment. The objective is to minimize resource usage, implying low capital expenditure and low operational cost, while satisfying expected increasing traffic needs. Better network design and dimensioning algorithms will enable providers to meet their customers demands far more quickly and cost-effectively. The research entails using an accurate model of physical-layer impairments within the design and management of translucent EONs. By using a network-state-dependent performance prediction instead of the transmission reach in the routing and resource allocation procedure, significant spectral and equipment savings can be gained. This cross-layer approach trades off computational complexity for increased resource usage efficiency. The research agenda begins by modifying the currently popular Gaussian-noise model for physical layer impairments for modern long-haul networks to be easily computed as a function of the network state. Then the project addresses the design of long-haul EONs by solving two fundamental problems:- Algorithm design for routing and resource allocation based on accurate physical impairment estimation; classical approaches to solving this problem have relied on worst case estimates that significantly overprovision the network. - Theoretical models for EON behavior in the presence of network-dependent physical layer impairments;the goal is to abstract physical layer parameters to make resource allocation calculations more tractable and less sensitive to small changes in those parameters. The project will be performed in collaboration with a research team at Nokia Bell Labs to ensure industrial relevance of the work.
期刊论文(12)
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Physical-layer impairment estimation for arbitrary spectral-shaped signals in optical networks
光网络中任意频谱形状信号的物理层损伤估计
DOI:
10.1364/oe.451806
发表时间:
2022
期刊:
Optics Express
影响因子:
3.8
作者:
[Xu, Yuxin, Brandt-Pearce, Maite]
通讯作者:
Brandt-Pearce, Maite
Cross-layer static resource provisioning for dynamic traffic in flexible grid optical networks
灵活网格光网络中动态流量的跨层静态资源配置
DOI:
10.1364/jocn.404693
发表时间:
2021
期刊:
Journal of Optical Communications and Networking
影响因子:
5
作者:
[Xu, Yuxin, Agrell, Erik, Brandt-Pearce, Maite]
通讯作者:
Brandt-Pearce, Maite
Iterative Resource Allocation Algorithm for EONs Based on a Linearized GN Model
基于线性化GN模型的EON迭代资源分配算法
DOI:
10.1364/jocn.11.000039
发表时间:
2019
期刊:
Journal of Optical Communications and Networking
影响因子:
5
作者:
[Xu, Yuxin, Yan, Li, Agrell, Erik, Brandt-Pearce, Maïté]
通讯作者:
Brandt-Pearce, Maïté
Regenerator Allocation in Nonlinear Elastic Optical Networks With Random Data Rates
具有随机数据速率的非线性弹性光网络中的再生器分配
DOI:
10.1364/ofc.2018.th2a.47
发表时间:
2018
期刊:
Optical Fiber Conference
影响因子:
--
作者:
[Yan, L., Xu, Y., Brandt-Pearce, M., Dharmaweera, N., Agrell, E.]
通讯作者:
Agrell, E.
DOI:
10.1364/cleo_at.2022.jw3b.106
发表时间:
2022
期刊:
CLEO 2022
影响因子:
--
作者:
[Xu, Yuxin, Brandt-Pearce, Maite]
通讯作者:
Brandt-Pearce, Maite
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