A5103092575- Optical Network Technologies
- Advanced Optical Network Technologies
- Advanced Photonic Communication Systems
- Photonic and Optical Devices
- Privacy-Preserving Technologies in Data
- Semiconductor Lasers and Optical Devices
- Software-Defined Networks and 5G
- Cryptography and Data Security
- PAPR reduction in OFDM
- Advanced Fiber Laser Technologies
- Internet Traffic Analysis and Secure E-voting
- IoT and Edge/Fog Computing
- Stochastic Gradient Optimization Techniques
- Peer-to-Peer Network Technologies
- Blockchain Technology Applications and Security
- Optical Wireless Communication Technologies
- Wireless Body Area Networks
- Digital Transformation in Industry
- Mobile Crowdsensing and Crowdsourcing
- Blind Source Separation Techniques
- Digital Mental Health Interventions
- Orbital Angular Momentum in Optics
- Optical Coherence Tomography Applications
- Machine Learning and ELM
- Electrostatic Discharge in Electronics
Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute
2019-2025
Universitat Politècnica de Catalunya
2014-2020
Fraunhofer Society
2020
Nokia (France)
2019
Athens Information Technology
2015-2018
University of California, Davis
2017
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo"
2017
Scuola Superiore Sant'Anna
2017
Iran University of Science and Technology
2015
We evaluate the advantages of using extra dimension introduced by space-division multiplexing (SDM) for dynamic bandwidth-allocation purposes in a flexible optical network. In that respect, we aim to compare spectral and spatial super-channel (Sp-Ch) allocation policies an SDM network based on bundles SMFs (to eliminate coupling between dimensions from study) investigate role modulation format selection blocking probability performance with emphasis efficiency (SE)/reach tradeoff different...
In elastic optical networks (EONs), effective soft failure localization is of paramount importance to early detection service level agreement violations while anticipating possible hard events. So far, techniques have been proposed and deployed mainly for failures, significant work still required provide automated solutions both during commissioning testing in-operation phases. this paper, we focus on in EONs by proposing two active monitoring passive monitoring. The rely specifically...
The availability of coarse-resolution cost-effective optical spectrum analyzers (OSAs) allows their widespread deployment in operators' networks. In this paper, we explore several machine learning approaches for soft-failure detection, identification, and localization that take advantage OSAs. particular, present three different solutions the two most common filter-related soft-failures: filter shift tight filtering, which noticeably deform expected shape spectrum. However, cascading is a...
Machine Learning (ML) is considered a promising tool to aid and accelerate diagnosis in various medical areas, including neuroimaging. However, its success set back by the lack of large-scale public datasets. Indeed, institutions possess large amount data; however, open-sourcing prevented legal requirements protect patient's privacy. Federated (FL) viable alternative that can overcome this issue. This work proposes training an ML model for Alzheimer's Disease (AD) detection based on...
A successful migration from current C-band based optical networks to a multiband scenario primarily depends on the development of solutions that can reliably measure physical properties links over broad spectral transmission windows.Additionally, these must be capable delivering wavelength-dependent and spatially-resolved indicators empower network operators identify faults before they lead severe service disruptions.Recently, exploitation receiver digital signal processing as tool for...
Spatially integrated switching architectures have been recently investigated in an attempt to provide capability for networks based on spatial division multiplexing (SDM) fibers, as well reduce the implementation cost. These rely following paradigms, furnishing different degrees of spectral and granularity: independent switching, which offers full spatial-spectral flexibility; joint-switching, treats all modes a single entity; fractional-joint whereby subgroups are switched together units....
Autonomic optical transmission and networking requires machine learning (ML) models to be trained with large datasets. However, the availability of enough real data produce accurate ML is rarely ensured since new equipment techniques are continuously being deployed in network. One option generate from simulations lab experiments, but such could not cover whole features space would translate into inaccuracies models. In this paper, we propose an ML-based algorithm life cycle facilitate...
We compare SDM joint and independent switching strategies in a planning scenario involving European backbone network. Joint can achieve cost savings of 40-50% with performance similar to that switching.
In this work, we compare the performance of several space division multiplexing (SDM) network realizations utilizing different types transmission media. regard, first present a tool developed for estimation signal quality degradation in SDM-based optical networks. The supports SDM networks few-mode fibers (FMFs) and multicore (MCFs), as well bundles single-mode (BuSMFs), provides an accurate (QoT) allowing operators designers to take into account physical layer impairments while performing...
In this work, efficient routing, spectrum, and core allocation (RSCA) techniques are proposed for spatial division multiplexed (SDM) elastic optical networks (EONs) utilizing multicore fibers (MCFs). These provide resource utilization with minimal computational complexity, while also taking into consideration physical layer effects. Initially, a crosstalk- aware approach is presented that accounts the crosstalk effects in network can have detrimental impact on connections established...
Background Pre-existing long-term health conditions are highly prevalent in people living with dementia. There is an established relationship between these conditions, trajectories of decline and outcomes dementia post-diagnosis. An understanding when first occur how they manifest over time within populations remains unclear. The pathophysiology across major bodily systems changes before after the clinical onset However, timing various complex, chronic interact their association not yet...
Space division multiplexing (SDM) is a promising approach to overcome the looming fiber capacity crunch. Joint and fractional joint switching (JoS FJoS) architectures, which switch multiple spatial dimensions together as atomic units, have been proposed reduce cost of implementing SDM cater strongly coupled transmission media. However, they shown impose significant penalties overall network performance, at least when many relatively small connections are used in context uncoupled dimensions,...
Data centers are continuously growing in scale and can contain more than one million servers spreading across thousands of racks; requiring a large-scale switching network to provide broadband reconfigurable interconnections low latency. Traditional data center architectures, through the use electrical packet switches multi-tier topology, has fundamental weaknesses such as oversubscription cabling complexity. Wireless intra-data interconnection solutions have been proposed deal with problem...
We apply deep graph convolutional neural networks for Quality-of-Transmission estimation of unseen network states capturing, apart from other important impairments, the inter-core crosstalk that is prominent in optical operating with multicore fibers.
The H2020 METRO-HAUL European project has architected a latency-aware, cost-effective, agile, and programmable optical metro network. This includes the design of semidisaggregated nodes with compute storage capabilities, which interface effectively both 5G access multi-Tbit/s elastic networks in core. In this paper, we report automated deployment services, particular, public safety video surveillance use case employing low-latency object detection tracking using on-camera on-the-edge...
The idea behind flexible optical transmission is to optimize the use of fiber capacity by flexibly assigning spectrum and data rate adapted needs end-to-end connection requests. Several techniques have been proposed this end. One such technique based on utilization Nyquist-shaping filters with aim reducing required channel spacing in single-carrier super-channel systems. Nonetheless, imperfect shape used at bandwidth-variable transceivers wavelength-selective switches compels necessity...
We compare different architectures of CD and CDC ROADMs supporting spatial superchannel routing in terms required components, revealing the most cost-effective designs.
In this paper, we study the quality of transmission (QoT) aware routing, modulation level, and resource assignment problem for transparent flexible optical networks over few-mode multi-core fibers. We consider two three-dimensional (3DRA) algorithms, called liberal conservative, that are compatible with fractional joint switching. The three dimensions core, mode, spectrum. Furthermore, analyze modulation-level selection (MLS) algorithms (one on-line one off-line) path (favoring shortest...
The availability of coarse-resolution cost-effective Optical Spectrum Analyzers (OSA) allows its widespread deployment in operators' networks. In this paper, several machine learning approaches for failure identification and localization that take advantage OSAs are presented.
Machine learning (ML)-assisted solutions for quality of transmission (QoT) estimation or classification have received significant attention in recent years. However, due to the unavailability large and well-structured datasets, individual research groups need create use their own datasets validating proposed solutions. Therefore, reported results (obtained using different datasets) are difficult reproduce hardly comparable. Regardless this limitation, a technique be followed by...
The power consumption of MIMO-DSP for SDM networks is investigated, assuming emerging sub-20-nm CMOS technology. Significant limitations on the network performance are revealed when scaling to large MIMO multiplicity (i.e. 12×12).