Muhammad Umar Masood
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View article: Intelligent Detection of Overlapping Fiber Anomalies in Optical Networks Using Machine Learning
Intelligent Detection of Overlapping Fiber Anomalies in Optical Networks Using Machine Learning Open
We propose a machine learning approach leveraging state-of-polarization dynamics to detect overlapping fiber anomalies. Simulated disturbances and XGBoost classification achieve near-perfect accuracy under noise, enabling precise identific…
View article: Statistical Evaluation of Lightpath Feasibility in Converged Optical Metro-Access Networks
Statistical Evaluation of Lightpath Feasibility in Converged Optical Metro-Access Networks Open
This paper analyzes the feasible Bit Error Rate (BER) for all lightpaths in a converged metro-access network. By modeling physical impairments across segments, it builds a statistical BER profile, enabling evaluation of signal integrity an…
View article: Capacity Assessment in Converged Metro-Access Optical Networks for end-to-end RAN Fronthaul
Capacity Assessment in Converged Metro-Access Optical Networks for end-to-end RAN Fronthaul Open
In this paper, we present a capacity and feasibility analysis of converged metro-access optical networks for supporting Radio Access Network (RAN) fronthauling, based on Bit Error Rate (BER) profiling. Using two commercially available tran…
View article: Demonstration of Real-Time AI-Enabled Smart Fault Detection using State-of-Polarization Monitoring
Demonstration of Real-Time AI-Enabled Smart Fault Detection using State-of-Polarization Monitoring Open
In this demo, we present a real-time, machine-learning-driven framework for early fault detection in optical fiber networks, leveraging continuous State-of-Polarization (SOP) monitoring and angular speed (SOPAS) analysis. By extracting pol…
View article: Resilient Anomaly Detection in Fiber-Optic Networks: A Machine Learning Framework for Multi-Threat Identification Using State-of-Polarization Monitoring
Resilient Anomaly Detection in Fiber-Optic Networks: A Machine Learning Framework for Multi-Threat Identification Using State-of-Polarization Monitoring Open
We present a thorough machine-learning framework based on real-time state-of-polarization (SOP) monitoring for robust anomaly identification in optical fiber networks. We exploit SOP data under three different threat scenarios: (i) malicio…
View article: Resilient Anomaly Detection in Fiber-Optic Networks: A Machine Learning Framework for Multi-Threat Identification Using State-of-Polarization Monitoring
Resilient Anomaly Detection in Fiber-Optic Networks: A Machine Learning Framework for Multi-Threat Identification Using State-of-Polarization Monitoring Open
We present a thorough machine-learning framework based on real-time state of polarization (SOP) monitoring for robust anomaly identification in optical fiber networks. We exploit SOP data under three different threat scenarios: (i) malicio…
View article: Network Data Based Transfer Learning Failure Prediction Agent Pre-Trained Using Digital Twin
Network Data Based Transfer Learning Failure Prediction Agent Pre-Trained Using Digital Twin Open
This paper describes the use of Transfer Learning (TL) using experimental data and a Machine Learning (ML) model pre-trained with a Digital Twin (DT) for the prediction of amplifier failures in optical networks. Using GNPy, an open-source …
View article: Design and performance assessment of modular multi-band photonic-integrated WSS
Design and performance assessment of modular multi-band photonic-integrated WSS Open
Today, optical transport and data center networks extensively utilize photonic integrated systems due to their large bandwidth and a high degree of reconfigurability. In addition to these properties, photonic integrated-based systems can d…
View article: Performance evaluation of data-driven techniques for the softwarized and agnostic management of an N×N photonic switch
Performance evaluation of data-driven techniques for the softwarized and agnostic management of an N×N photonic switch Open
The emerging Software Defined Networking (SDN) paradigm paves the way for flexible and automatized management at each layer. The SDN-enabled optical network requires each network element’s software abstraction to enable complete control by…
View article: Performance Evaluation of Data-DrivenTechniques for Softwarized and AgnosticManagement of N×N Photonic Switch
Performance Evaluation of Data-DrivenTechniques for Softwarized and AgnosticManagement of N×N Photonic Switch Open
The emerging Software Defined Networking (SDN) paradigm paves the way for flexible and automatized management at each layer. The SDN-enabled optical network requires each network element’s software abstraction to enable complete control by…
View article: Convolutional neural network for quality of transmission prediction of unestablished lightpaths
Convolutional neural network for quality of transmission prediction of unestablished lightpaths Open
With the advancement in evolving concepts of software‐defined networks and elastic‐optical‐network, the number of design parameters is growing dramatically, making the lightpath (LP) deployment more complex. Typically, worst‐case assumptio…
View article: Automatic Management of <i>N</i> × <i>N</i> Photonic Switch Powered by Machine Learning in Software-Defined Optical Transport
Automatic Management of <i>N</i> × <i>N</i> Photonic Switch Powered by Machine Learning in Software-Defined Optical Transport Open
Optical networking is fast evolving towards the applications of the Software-defined Networking (SDN) paradigm down to the (Wavelength-division Multiplexing) WDM transport layer for cost-effective and flexible infrastructure management. Op…