Physical-Layer Awareness: GNPy and ONOS for End-to-End Circuits in Disaggregated Networks

Kundrát, Jan; Campanella, Andrea; Rouzic, Esther Le; Ferrari, Alessio; Havliš, Ondřej; Hazlinsky, Michal; Grammel, Gert; Galimberti, Gabriele; Curri, Vittorio

doi:10.1364/ofc.2020.m3z.17

Cited by 11 publications

(7 citation statements)

References 5 publications

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“…As the ASE noise has a great contribution in the GSNR calculation, an accurate model of the amplifier is necessary. GNPy has been utilized with ONOS SDN controller as a path computation engine [18] and also as a tool for operators optimize their procurement processes as GNPY serves to compare performance from different vendors. GNPy has also been featured as a path computation engine (PCE) in a collaborative effort within TIP converged architecture for Network Disaggregation and Integration [19].…”

Section: A Gaussian Noise Simulation In Python (Gnpy)mentioning

confidence: 99%

Disaggregated Optical Networks: A Survey

Cruzes

2024

Preprint

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Section: A Gaussian Noise Simulation In Python (Gnpy)mentioning

confidence: 99%

Disaggregated Optical Networks: A Survey

Cruzes

2024

Preprint

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“…Recently, a remarkable number of works have addressed the capabilities and the potentials of SDN controllers to enable disaggregation at the optical layer. Kundrat et al [20] showed an automatic provisioning workflow over a multi-vendor optical line system and a Cassini transceiver that included the optical impairment estimation phase, using the ONOS Controller. Giorgetti et al [5] conducted an overall analysis of the ONOS performances related to the optical connection provisioning and restoration in a 7-node disaggregated network scenario, highlighting the issues of the ONOS Controller regarding the recovery reaction.…”

Section: Related Workmentioning

confidence: 99%

Scalable OneM2M IoT Open-Source Platform Evaluated in an SDN Optical Network Controller Scenario

Troscia

Sgambelluri

Paolucci

et al. 2022

Sensors

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Software Defined Networking represents a mature technology for the control of optical networks, though all open controller implementations present in the literature still lack the adequate level of maturity and completeness to be considered for (pre)-production network deployments. This work aims at experimenting on, assessing and discussing the use of the OneM2M open-source platform in the context of optical networks. Network elements and devices are implemented as IoT devices, and the control application is built on top of an OneM2M-compliant server. The work concretely addresses the scalability and flexibility performances of the proposed solution, accounting for the expected growth of optical networks. The two experiment scenarios show promising results and confirm that the OneM2M platform can be adopted in such a context, paving the way to other researches and studies.

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“…In particular, [31] reports the GNPY validation in a mixed-fibre test-bed at Microsoft labs in which transponders of eight different manufacturers operated in the C-band reaching a propagation distance of 1945 km. Relevantly, GNPY has also been considered as an assistance tool for the computation of impairments in optical-layer paths on top of SDN controllers [32]. Nonetheless, these efforts are scarce in the literature because optical-layer awareness is commonly considered as stand-alone planning tools separated from operational aspects addressed by SDN controllers.…”

Section: State Of the Artmentioning

confidence: 99%

Emulating Software-Defined Disaggregated Optical Networks in a Containerized Framework

et al. 2021

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Telecom operators’ infrastructure is undergoing high pressure to keep the pace with the traffic demand generated by the societal need of remote communications, bandwidth-hungry applications, and the fulfilment of 5G requirements. Software-defined networking (SDN) entered in scene decoupling the data-plane forwarding actions from the control-plane decisions, hence boosting network programmability and innovation. Optical networks are also capitalizing on SDN benefits jointly with a disaggregation trend that holds the promise of overcoming traditional vendor-locked island limitations. In this work, we present our framework for disaggregated optical networks that leverages on SDN and container-based management for a realistic emulation of deployment scenarios. Our proposal relies on Kubernetes for the containers’ control and management, while employing the NETCONF protocol for the interaction with the light-weight software entities, i.e., agents, which govern the emulated optical devices. Remarkably, our agents’ structure relies on components that offer high versatility for accommodating the wide variety of components and systems in the optical domain. We showcase our proposal with the emulation of an 18-node European topology employing Cassini-compliant optical models, i.e., a state-of-the-art optical transponder proposed in the Telecom Infrastructure Project. The combination of our versatile framework based on containerized entities, the automatic creation of agents and the optical-layer characteristics represents a novel approach suitable for operationally complex carrier-grade transport infrastructure with SDN-based disaggregated optical systems.

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Physical-Layer Awareness: GNPy and ONOS for End-to-End Circuits in Disaggregated Networks

Abstract: This demo shows the automatic end-to-end path provisioning over a multi-vendor fully disaggregated Open Line System by Czech Light using the GNPy QoT estimator and Cassini transceiver by the Telecom Infra Project integrated with ONOS.

Cited by 11 publications

References 5 publications

Disaggregated Optical Networks: A Survey

Disaggregated Optical Networks: A Survey

Scalable OneM2M IoT Open-Source Platform Evaluated in an SDN Optical Network Controller Scenario

Emulating Software-Defined Disaggregated Optical Networks in a Containerized Framework

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