Robust Regenerator Allocation in Nonlinear Flexible-Grid Optical Networks With Time-Varying Data Rates

Li, Yan; Xu, Yuxin; Brandt-Pearce, Maïté; Dharmaweera, Nishan; Agrell, Erik

doi:10.1364/jocn.10.000823

Cited by 12 publications

(8 citation statements)

References 25 publications

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“…In this paper, we consider the widely applied transmission reach (TR) model as the benchmark. The TR model is conservative and estimates the worst-case noise for demands [6,8,14,21]. The so-called Gaussian noise (GN) model is one of the most widely-applied PLI estimates with low complexity and acceptable accuracy.…”

Section: Modeling Pli For An Overlapped Spectrum Assignmentmentioning

confidence: 99%

“…The PSGN model is used in Algorithm 2 as follows. G RC , the set of PLIs, comprises the PLI estimate G q,l (per span per polarization) for each demand q ∈ D RC and link l ∈ U q , computed by the noise estimated in (8), where…”

Section: Modeling Pli For An Overlapped Spectrum Assignmentmentioning

confidence: 99%

“…In recently proposed offline resource provisioning algorithms for time-varying traffic [3,[8][9][10], time is considered an extra optimization dimension. These algorithms perform a flexible resource allocation based on a highly-scalable dynamic resource assignment while considering the comprehensive interests of multiple consecutive time periods (overall interests within the time frames).…”

Section: Introductionmentioning

confidence: 99%

“…In [8,9], the authors proposed using the statistical network assignment process (SNAP) algorithm based on Monte Carlo simulations to obtain the expected network state. The traffic's data-rate is randomly selected in each simulation trial (also considered as a time period), and then network resources are assigned by a static network planning algorithm for the randomlyselected traffic state.…”

Section: Introductionmentioning

confidence: 99%

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Cross-layer static resource provisioning for dynamic traffic in flexible grid optical networks

Agrell

Brandt-Pearce

2021

J. Opt. Commun. Netw.

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Flexible grid networks need rigorous resource planning to avoid network over-dimensioning and resource over-provisioning. The network must provision the hardware and spectrum resources statically, even for dynamic random bandwidth demands, due to the infrastructure of flexible grid networks, hardware limitations, and the reconfiguration speed of the control plane. We propose a flexible-online-offline probabilistic (FOOP) algorithm for the static spectrum assignment of random bandwidth demands. The FOOP algorithm considers the probabilistic nature of random bandwidth demands and balances hardware and control plane pressures with spectrum assignment efficiency. The FOOP algorithm uses the probabilistic spectrum Gaussian noise (PSGN) model to estimate the physical-layer impairment (PLIs) for random bandwidth traffic. Compared to a benchmark spectrum assignment algorithm and a widely applied PLI estimation model, the proposed FOOP algorithm using the PSGN model saves up to 49% of network resources.

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Section: Modeling Pli For An Overlapped Spectrum Assignmentmentioning

confidence: 99%

Section: Modeling Pli For An Overlapped Spectrum Assignmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Cross-layer static resource provisioning for dynamic traffic in flexible grid optical networks

Agrell

Brandt-Pearce

2021

J. Opt. Commun. Netw.

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“…In a recent work, the authors [29] presented a heuristic RWA algorithm to identify minimum number of the regeneration sites. In [30], the problem of allocating regenerators in flexible-grid optical networks is studied.…”

Section: Related Workmentioning

confidence: 99%

Minimizing Cost of Regeneration at Regeneration Sites–A New Approach for Dynamic Lightpath Establishment in Translucent Optical Networks

et al. 2020

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Lightpaths in translucent optical networks have to undergo regeneration at certain nodes designated as regeneration sites to maintain its quality of transmission. Regenerating an optical signal necessitates optical-electronic-optical conversion and is thus a costly affair due to use of regeneration resources. Thus minimizing the cost of regeneration in such networks is vital. Minimizing cost of regeneration leads to two different problems; 1) the problem of minimizing the total cost of regeneration for the connections served and 2) the problem of minimizing the cost of regeneration at regeneration sites while serving the connections. The previous works on lightpath establishment in such networks have mostly addressed the first problem. In this paper we study the second problem i.e. the problem of minimizing the cost of regeneration at regeneration sites during dynamic establishment of lightpaths. As the problem is NP-Complete, we propose an Integer Linear Program for small networks and then propose two heuristic routing approaches for large networks. Time complexity analysis shows that our heuristic algorithms run in polynomial time. Extensive simulation experiments reveal that our approaches are not only efficient to address the problem but can also provide better blocking performance when regeneration resources are scarcely deployed at regeneration sites. INDEX TERMS Dynamic routing, minimizing regeneration, regeneration sites, translucent optical networks, wavelength assignment.

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Assessment of novel regenerator assignment strategies in dynamic translucent elastic optical networks

et al. 2019

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Robust Regenerator Allocation in Nonlinear Flexible-Grid Optical Networks With Time-Varying Data Rates

Cited by 12 publications

References 25 publications

Cross-layer static resource provisioning for dynamic traffic in flexible grid optical networks

Cross-layer static resource provisioning for dynamic traffic in flexible grid optical networks

Minimizing Cost of Regeneration at Regeneration Sites–A New Approach for Dynamic Lightpath Establishment in Translucent Optical Networks

Assessment of novel regenerator assignment strategies in dynamic translucent elastic optical networks

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