135 citations · 299 across the 10 of their papers we have counts for
10 papers
Fault Monitoring in Passive Optical Networks using Machine Learning Techniques
Khouloud Abdelli, Carsten Tropschug, Helmut Griesser +1
Passive optical network (PON) systems are vulnerable to a variety of failures, including fiber cuts and optical network unit (ONU) transmitter/receiver failures. Any service interr…
Faulty Branch Identification in Passive Optical Networks using Machine Learning
Khouloud Abdelli, Carsten Tropschug, Helmut Griesser +1
Passive optical networks (PONs) have become a promising broadband access network solution. To ensure a reliable transmission, and to meet service level agreements, PON systems have…
Branch Identification in Passive Optical Networks using Machine Learning
khouloud Abdelli, Carsten Tropschug, Helmut Griesser +2
A machine learning approach for improving monitoring in passive optical networks with almost equidistant branches is proposed and experimentally validated. It achieves a high diagn…
DeepALM: Holistic Optical Network Monitoring based on Machine Learning
Joo Yeon Cho, Jose-Juan Pedreno-Manresa, Sai Kireet Patri +4
We demonstrate a machine learning-based optical network monitoring system which can integrate fiber monitoring, predictive maintenance of optical hardware, and security information…
Machine Learning-based Anomaly Detection in Optical Fiber Monitoring
Khouloud Abdelli, Joo Yeon Cho, Florian Azendorf +3
Secure and reliable data communication in optical networks is critical for high-speed Internet. However, optical fibers, serving as the data transmission medium providing connectiv…
Reflective Fiber Faults Detection and Characterization Using Long-Short-Term Memory
Khouloud Abdelli, Helmut Griesser, Peter Ehrle +2
To reduce operation-and-maintenance expenses (OPEX) and to ensure optical network survivability, optical network operators need to detect and diagnose faults in a timely manner and…
Optical Fiber Fault Detection and Localization in a Noisy OTDR Trace Based on Denoising Convolutional Autoencoder and Bidirectional Long Short-Term Memory
Khouloud Abdelli, Helmut Griesser, Carsten Tropschug +1
Optical time-domain reflectometry (OTDR) has been widely used for characterizing fiber optical links and for detecting and locating fiber faults. OTDR traces are prone to be distor…
Gated Recurrent Unit based Autoencoder for Optical Link Fault Diagnosis in Passive Optical Networks
Khouloud Abdelli, Florian Azendorf, Helmut Griesser +2
We propose a deep learning approach based on an autoencoder for identifying and localizing fiber faults in passive optical networks. The experimental results show that the proposed…
ML-based Anomaly Detection in Optical Fiber Monitoring
Khouloud Abdelli, Joo Yeon Cho, Carsten Tropschug
Secure and reliable data communication in optical networks is critical for high-speed internet. We propose a data driven approach for the anomaly detection and faults identificatio…
A BiLSTM-CNN based Multitask Learning Approach for Fiber Fault Diagnosis
Khouloud Abdelli, Helmut Griesser, Carsten Tropschug +1
A novel multitask learning approach based on stacked bidirectional long short-term memory (BiLSTM) networks and convolutional neural networks (CNN) for detecting, locating, charact…