Performance analysis of QoT estimator in SDN-controlled ROADM networks

Diaz-Montiel, Alan A.; Yu, Jiakai; Mo, Weiyang; Li, Yao; Kilper, Daniel C.; Ruffini, Marco

doi:10.23919/ondm.2018.8396121

Cited by 8 publications

(6 citation statements)

References 21 publications

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“…Although hardware testbeds offer ground truth and line rate performance, they are often expensive, hard to reconfigure, and limited in size. The development of innovative optical SDN systems such as ODTN [2] could benefit greatly from a flexible and scalable open source software emulator that emulates the physical, data, and control planes for packet-optical networks [3], much as the Mininet [4] emulator does for packet networks.…”

Section: Overviewmentioning

confidence: 99%

Demonstration of Software-Defined Packet-Optical Network Emulation with Mininet-Optical and ONOS

Lantz¹,

Diaz-Montiel²,

Yu³

et al. 2020

Optical Fiber Communication Conference (OFC) 2020

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Section: Overviewmentioning

confidence: 99%

Demonstration of Software-Defined Packet-Optical Network Emulation with Mininet-Optical and ONOS

Lantz¹,

Diaz-Montiel²,

Yu³

et al. 2020

Optical Fiber Communication Conference (OFC) 2020

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“…For the purposes of this study, we used the customized Optical-MAN simulator first introduced in [13], which allows to deploy WDM network topologies and collect synthetic labeled data to train ML models, as we recently presented in [11] for the analysis of support vector machines (SVM). Our tool simulates WDM networks considering: optical nodes consisting of ROADMs equipped with WSSs, optically-amplified AGC-EDFA links, and also AGC-EDFAs for pre-/post-signal amplification, together with fiber non-linear effects such as stimulated Raman scattering.…”

Section: A System Setupmentioning

confidence: 99%

“…For the execution of the experiments, we used Table 1. the Scikit-learn: Machine Learning in Python software [12], which provides powerful APIs for ML classification models. Then, for the data generation, we used the Optical-MAN simulator first introduced in [13], which allows for the creation of large scale optical networks deployed with WSS-based ROADMs and EDFA-amplified links, and the simultaneous transmission of 90 channels in the C-band spectrum (1529.6 nm -1565.2 nm).…”

Section: Introductionmentioning

confidence: 99%

A Performance Analysis of Supervised Learning Classifiers for QoT Estimation in ROADM-Based Networks

Diaz-Montiel

Ruffini

2020

Optical Network Design and Modeling

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Machine learning techniques for optimization purposes in the optical domain have been reviewed extensively in recent years. While several studies are pointing in the right direction towards building enhanced transport network control systems including estimation algorithms, the physical effects encountered in the optical domain raise several challenges that are hard to learn from and mitigate. In this paper, we provide a performance analysis of various supervised learning algorithms when predicting the Quality of Transmission (QoT), in terms of signal to noise ratio (OSNR), of lightpaths when erbium doped fiber amplifier (EDFA) power excursions and fiber nonlinearities are taken into account. The analysis considers F1-scores and computational training times as the main comparison metrics. A customized optical data network simulator was used for the generation of synthetic labeled data samples. Our results depict similar performance among groups of classifiers, and a correlation between the data sample size and the prediction accuracy.

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“…One of them is PathMon [60], which provides granular traffic monitoring. Another one is a QoT estimator for ROADM networks implemented and evaluated in [61].…”

Section: Poc Implementationsmentioning

confidence: 99%

The Road to BOFUSS: The Basic OpenFlow User-space Software Switch

Fernandes¹,

Rojas²,

Alvarez-Horcajo³

et al. 2019

Preprint

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Software switches are pivotal in the Software-Defined Networking (SDN) paradigm, particularly in the early phases of development, deployment and testing. Currently, the most popular one is Open vSwitch (OVS), leveraged in many production-based environments. However, due to its kernel-based nature, OVS is typically complex to modify when additional features or adaptation is required. To this regard, a simpler user-space is key to perform these modifications. In this article, we present a rich overview of BOFUSS, the basic Open-Flow user-space software switch. BOFUSS has been widely used in the research community for diverse reasons, but it lacked a proper reference document. For this purpose, we describe the switch, its history, architecture, uses cases and evaluation, together with a survey of works that leverage this switch. The main goal is to provide a comprehensive overview of the switch and its characteristics. Although the original BO-FUSS is not expected to surpass the high performance of OVS, it is a useful complementary artifact that provides some OpenFlow features missing in OVS and it can be easily modified for extended functionality. Moreover, enhancements provided by the BEBA project brought the performance from BOFUSS close to OVS. In any case, this paper sheds light to researchers looking for the trade-offs between performance and customization of BOFUSS.

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Performance analysis of QoT estimator in SDN-controlled ROADM networks

Cited by 8 publications

References 21 publications

Demonstration of Software-Defined Packet-Optical Network Emulation with Mininet-Optical and ONOS

Demonstration of Software-Defined Packet-Optical Network Emulation with Mininet-Optical and ONOS

A Performance Analysis of Supervised Learning Classifiers for QoT Estimation in ROADM-Based Networks

The Road to BOFUSS: The Basic OpenFlow User-space Software Switch

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