Ting Wang NEC Labs America

Ting Wang

Department Head

Optical Networking & Sensing

Posts

Semi-Automatic Line-System Provisioning with Integrated Physical-Parameter-Aware Methodology: Field Verification and Operational Feasibility

/in /by

We propose methods and architecture to conduct measurements and optimize newly installed optical fiber line systems semi-automatically using integrated physics-aware technologies in a data center interconnection (DCI) transmission scenario. We demonstrate, for the first time, digital longitudinal monitoring (DLM) and optical line system (OLS) physical parameter calibration working together in real-time to extract physical link parameters for transmission performance optimization. Our methodology has the following advantages over traditional design: minimized footprint at the user site, accurate estimate of necessary optical network characteristics via complementary telemetry technologies, and ability to conduct all operation work from remotely. The last feature is crucial as remote operation personnel can implement network design settings for immediate response to quality of transmission (QoT) degradation and reverting in case of unforeseen problems. We successfully completed the semi-automatic line system provisioning over field fiber networks facilities at Duke University, Durham, NC. The tasks of parameter retrieval, equipment setting optimization, and system setup/provisioning were completed within 1 hour. The field operation was supervised by on-duty personnel who can access the system remotely from different timezones. By comparing Q-factor estimates calculated by the extracted link parameters with measured results from 400G transceivers, we confirmed our methodology has a reduction in the QoT prediction errors overexisting design.

Read more

NEC Labs America at OFC 2024 San Diego from March 24 – 28

/in /by

The NEC Labs America team Yaowen Li, Andrea D’Amico, Yue-Kai Huang, Philip Ji, Giacomo Borraccini, Ming-Fang Huang, Ezra Ip, Ting Wang & Yue Tian (Not pictured: Fatih Yaman) has arrived in San Diego, CA for OFC24! Our team will be speaking and presenting throughout the event. Read more for an overview of our participation.

Read more

Optical Network Anomaly Detection and Localization Based on Forward Transmission Sensing and Route Optimization

/in /by

We introduce a novel scheme to detect and localize optical network anomaly using forward transmission sensing, and develop a heuristic algorithm to optimize the route selection. The performance is verified via simulations and network experiments.

Read more

Optical Line Physical Parameters Calibration in Presence of EDFA Total Power Monitors

/in /by

A method is proposed in order to improve QoT-E by calibrating the physical model parameters of an optical link post-installation, using only total power monitors integrated into the EDFAs and an OSA at the receiver.

Read more

Multi-Span Optical Power Spectrum Prediction using ML-based EDFA Models and Cascaded Learning

/in /by

We implement a cascaded learning framework using component-level EDFA models for optical power spectrum prediction in multi-span networks, achieving a mean absolute error of 0.17 dB across 6 spans and 12 EDFAs with only one-shot measurement.

Read more

Modeling the Input Power Dependency in Transceiver BER-ONSR for QoT Estimation

/in /by

We propose a method to estimate the input power dependency of the transceiver BER-OSNR characteristic. Experiments using commercial transceivers show that estimation error in Q-factor is less than 0.2 dB.

Read more

Field Implementation of Fiber Cable Monitoring for Mesh Networks with Optimized Multi-Channel Sensor Placement

/in /by

We develop a heuristic solution to effectively optimize the placement of multi-channel distributed fiber optic sensors in mesh optical fiber cable networks. The solution has beenimplemented in a field network to provide continuous monitoring.

Read more

Distributed Fiber Optic Sensing for Fault Localization Caused by Fallen Tree Using Physics-informed ResNet

/in /by

Falling trees or their limbs can cause power lines to break or sag, sometimes resulting in devastating wildfires. Conventional protections such as circuit breakers, overcurrent relays and automatic circuit reclosers may clear short circuits caused by tree contact, but they may not detect cases where the conductors remain intact or a conducting path is not sufficient to create a full short circuit. In this paper, we introduce a novel, non-intrusive monitoring technique that detects and locates fallen trees, even if a short circuit is not triggered. This method employs distributed fiber optic sensing (DFOS) to detect vibrations along the power distribution line where corresponding fiber cables are installed. A physics-informed ResNet model is then utilized to interpret this information and accurately locate fallen trees, which sets it apart from traditional black-box predictions of machine learning algorithms. Our real-scale lab tests demonstrate highly accurate and reliable fallen tree detection and localization.

Read more

Fast WDM Provisioning With Minimum Probe Signals: The First Field Experiments For DC Exchanges

/in /by

There are increasing requirements for data center interconnection (DCI) services, which use fiber to connect any DC distributed in a metro area and quickly establish high-capacity optical paths between cloud services and mobile edge computing and the users. In such networks, coherent transceivers with various optical frequency ranges, modulators, and modulation formats installed at each connection point must be used to meet service requirements such as fast-varying traffic requests between user computing resources. This requires technologyand architectures that enable users and DCI operators to cooperate to achieve fast provisioning of WDM links and flexible route switching in a short time, independent of the transceiver’s implementation and characteristics. We propose an approach to estimate the end-to-end (EtE) generalized signal-to-noise ratio (GSNR) accurately in a short time, not by measuring the GSNR at the operational route and wavelength for the EtE optical path but by simply applying a quality of transmission probe channel link by link, at a wavelength/modulation-formatconvenient for measurement. Assuming connections between transceivers of various frequency ranges, modulators, and modulation formats, we propose a device software architecture in which the DCI operator optimizes the transmission mode between user transceivers with high accuracy using only common parameters such as the bit error rate. In this paper, we first implement software libraries for fast WDM provisioning and experimentally build different routes to verify the accuracy of this approach. For the operational EtE GSNR measurements, theaccuracy estimated from the sum of the measurements for each link was 0.6 dB, and the wavelength-dependent error was about 0.2 dB. Then, using field fibers deployed in the NSF COSMOS testbed, a Linux-based transmission device software architecture, and transceivers with different optical frequency ranges, modulators, andmodulation formats, the fast WDM provisioning of an optical path was completed within 6 min.

Read more

Seamless Service Handover in UAV-based Mobile Edge Computing

/in /by

Unmanned aerial vehicles (UAVs), such as drones, can carry high-performance computing devices (e.g., servers) to provide flexible and on-demand data processing services for theusers in the network edge, leading to the so-called mobile edge computing. In mobile edge computing, researchers have already explored how to optimize the computation offloading and the trajectory planning of UAVs, as well as how to perform the service handover when mobile users move from one location to another. However, there is one critical challenge that has been neglected in past research, which is the limited battery life of UAVs. On average, commercial-level drones only have a battery life of around 30 minutes to 2 hours. As a result, during operation, mobile edge computing carriers have to frequently deal with service handovers that require shifting users and their computing jobs from low-battery UAVs to new fully-charged UAVs. This is the first work that focuses on addressing this challenge with the goal of providing continuous and uninterrupted mobile edge computing service. In particular, we propose a seamless service handover system that achieves minimum service downtime when handling the duty shift between low-battery UAVs and new fullycharged UAVs. In addition, we propose a novel UAV dispatchalgorithm that provides guidelines about how to dispatch new fully-charged UAVs and where to retrieve low-battery UAVs, with the objective of maximizing UAVs’ service time. The effectiveness of the proposed service handover system and the proposed UAV dispatch algorithm is demonstrated through comprehensive simulations using a time-series event-driven simulator.

Read more