Quantum Key Distribution (QKD) over Software-Defined Optical Networks

Optical network security is attracting increasing research interest. Currently, software-defined optical network (SDON) has been proposed to increase network intelligence (e.g., flexibility and programmability) which is gradually moving toward industrialization. However, a variety of new threats are emerging in SDONs. Data encryption is an effective way to secure communications in SDONs. However, classical key distribution methods based on the mathematical complexity will suffer from increasing computational power and attack algorithms in the near future. Noticeably, quantum key distribution (QKD) is now being considered as a secure mechanism to provision information-theoretically secure secret keys for data encryption, which is a potential technique to protect communications from security attacks in SDONs. This chapter introduces the basic principles and enabling technologies of QKD. Based on the QKD enabling technologies, an architecture of QKD over SDONs is presented. Resource allocation problem is elaborated in detail and is classified into wavelength allocation, time-slot allocation, and secret key allocation problems in QKD over SDONs. Some open issues and challenges such as survivability, cost optimization, and key on demand (KoD) for QKD over SDONs are discussed

Machine learning-based routing and wavelength assignment in software-defined optical networks

Recently, machine learning (ML) has attracted the attention of both researchers and practitioners to address several issues in the optical networking field. This trend has been mainly driven by the huge amount of available data (i.e., signal quality indicators, network alarms, etc.) and to the large number of optimization parameters which feature current optical networks (such as, modulation format, lightpath routes, transport wavelength, etc.). In this paper, we leverage the techniques from the ML discipline to efficiently accomplish the routing and wavelength assignment (RWA) for an input traffic matrix in an optical WDM network. Numerical results show that near-optimal RWA can be obtained with our approach, while reducing computational time up to 93% in comparison to a traditional optimization approach based on integer linear programming. Moreover, to further demonstrate the effectiveness of our approach, we deployed the ML classifier into an ONOS-based software defined optical network laboratory testbed, where we evaluate the performance of the overall RWA process in terms of computational time.The authors would like to acknowl-edge the support of the project TEXEO (TEC2016-80339-R), funded by Spanish MINECO and the EU-H2020 Metrohaul project (grant no. 761727)

Flexible and Autonomous Multi-band Raman Amplifiers

We propose an embedded controller able to autonomously manage Raman amplification in software-defined optical networks. The conceived structure allows the system to work both in single and multi-band transmission, achieving a large range of amplification constraints. A set of experiments validates this proposal

Digital signal processing for sensing in software defined optical networks

Optical networks are moving from static point-to-point to dynamic configurations, where transmitter parameters are adaptively changing to meet traffic demands. Dynamic network reconfigurability is achievable through software-defined transceivers, capable of changing the data-rate, overhead, modulation format and reach. Additionally, flexibility in the spectral allocation of channels ensures that the available resources are efficiently distributed, as the increase in fibre capacity has reached a halt. The complexity of such highly reconfigurable systems and cost of their maintenance increase exponentially. Implemented as part of digital signal processing of coherent receivers, sensing is an enabling technology for future software defined optical networks, as it makes possible to both control and optimise transmission parameters, as well as to manage faulty links and mitigate channel impairments in a cost-effective manner. Symbol-rate is one of the parameters most likely to adaptively change according to existing fibre impairments, such as optical signal-to-noise ratio or chromatic dispersion. A single-channel symbol-rate estimation technique is demonstrated initially, yielding a sufficient accuracy to distinguish between different typical error-correction overheads, in the presence of dispersion and white Gaussian noise. Further increasing the capacity over fibre to 1 Tb/s and beyond means moving towards superchannel configurations that employ Nyquist pulse shaping to increase spectral efficiency. Novel sensing techniques applicable to such information dense configurations, that can jointly monitor the channel bandwidth, frequency offset, optical signal-to-noise ratio and chromatic dispersion are proposed and demonstrated herein. Based on time-domain and frequency-domain functions derived from the theory of cyclostationarity, the performance of this joint estimator is investigated with respect to a wide range of parameters. The required acquisition time of the receiver is approximately 6.55 μs, three orders of magnitude faster compared to the round-trip time in core networks. The pulse shaping at the transmitter limits the performance of this estimator, unless the excess bandwidth is 30% of the symbol-rate, or more

Overview of South-Bound Interfaces for Software-Defined Optical Networks

In SDN-enabled networks, the control plane and data plane interaction relies on open SouthBound Interfaces (SBIs) so that the SDN controller exercises direct control over the data plane elements. In this paper, we review current initiatives of SBI to control optical components which include ad-hoc extensions of OpenFlow and YANG modelling proposals combined with the NETCONF / RESTCONF protocols. Then we overview different tools and frameworks available for quick prototyping and deployment of software services that are compliant with such interfaces. Finally, we discuss the advantages and drawbacks of the reviewed initiatives considered key enablers for standardized end-to-end network programmability

Advanced Modulation Techniques for Flexible Optical Transceivers: The Rate/Reach Tradeoff

This tutorial paper reviews advanced modulation techniques that have been proposed in the literature for the implementation of flexible (or reconfigurable) transceivers, which are fundamental building blocks of next-generation software-defined optical networks. Using a common reference multi-span propagation system scenario, the performance of transceivers employing standard quadrature amplitude modulation with variable-rate forward error correction, probabilistic constellation-shaping, and time-domain hybrid formats is assessed, highlighting the achievable flexibility in terms of continuous tradeoff between transmission rate and distance. The combination of these techniques with sub-carrier multiplexing, which enables an increase of the fiber nonlinearity tolerance thanks to the optimization of the symbol rate per sub-carrier, is also discussed

Make-Before-Break Wavelength Defragmentation

International audienceFuture optical networks, in particular Software Defined Optical Networks (SDONs), are expected to provide reconfigurable services while maintaining an efficient usage of wavelength resources. In this paper, we propose a Make-Before-Break (MBB) wavelength defragmentation process which minimizes the bandwidth requirement of the resulting provisioning. We next compare the latter provisioning with a minimum bandwidth provisioning that is not subject to MBB. The resulting solution process is thoroughly tested on various data and network instances. Numerical experiments show that, on average, the best seamless lightpath rerouting is never more than 5% away (less than 1% on average) from an optimal lightpath provisioning