Root Cause Analysis of Optical Transport Network Channel Failure
| dc.contributor.advisor | Yalemzewd Negash (PhD) | |
| dc.contributor.author | Aziza Ahmed | |
| dc.date.accessioned | 2025-01-14T13:59:23Z | |
| dc.date.available | 2025-01-14T13:59:23Z | |
| dc.date.issued | 2024-08 | |
| dc.description.abstract | As demands for high bandwidth surge due to 4K/8K streaming, 5G networks, and cloud-based applications, robust optical transport networks (OTNs) are critical. OTN failures can significantly impact service quality, network availability, and service level agreements (SLAs). While research has addressed fault prediction and localization, a gap exists in root cause analysis (RCA) for OTN channel failures. This study proposes a novel approach utilizing machine learning (ML) to pinpoint the root cause of these failures efficiently. This study compared four ML classifier models to analyze real data from ethio telecom’s network. The data included eight key features that influence OTN channel performance. Extreme Gradient Boosting (XGBoost) emerged as the superior performer, achieving an impressive 99.91% accuracy and a high F1-score of 97.5%. Furthermore, it excelled in efficiency, with training times of just 5.42 seconds and testing times of 0.2 seconds. Interestingly, the model identified minimum input optical power (Min IOP) as the most critical factor, suggesting that extrinsic loss within the fiber optic cables is a major cause of OTN channel failures. This study explores a novel ML system for OTN RCA, enabling faster and more precise root cause identification. This empowers network operators to proactively address issues and ensure optimal performance, significantly boosting network reliability and efficiency in the high-bandwidth age. | |
| dc.identifier.uri | https://etd.aau.edu.et/handle/123456789/4109 | |
| dc.language.iso | en_US | |
| dc.publisher | Addis Ababa University | |
| dc.subject | OTN | |
| dc.subject | RCA | |
| dc.subject | Channel Failure | |
| dc.subject | Feature Importance | |
| dc.subject | XGBoost | |
| dc.subject | Min IOP | |
| dc.subject | SM Errored Second | |
| dc.subject | Extrinsic loss | |
| dc.title | Root Cause Analysis of Optical Transport Network Channel Failure | |
| dc.type | Thesis |