Abstract
Automation of mobile network fault diagnostics and troubleshooting is critical for successful transformation to new network technologies such as 5G and core Network Function Virtualization (NFV). This paper presents a decision tree-based call detail record (CDR) labeling process, which is used to construct an automated end-to-end diagnostics system for mobile network faults. The presented diagnostics system will enable the utilization of automated troubleshooting systems, and the execution of automated corrective actions in third party systems such as Self-Organizing Network (SON) and NFV domain orchestrator.
Original language | English |
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Title of host publication | 15th International Conference on Network and Service Management, CNSM 2019 |
Editors | Hanan Lutfiyya, Yixin Diao, Nur Zincir-Heywood, Remi Badonnel, Edmundo Madeira |
Publisher | IEEE |
Number of pages | 7 |
ISBN (Electronic) | 9783903176249 |
DOIs | |
Publication status | Published - Oct 2019 |
MoE publication type | A4 Article in a conference publication |
Event | International Conference on Network and Service Management - Halifax, Canada Duration: 21 Oct 2019 → 25 Oct 2019 Conference number: 15 |
Conference
Conference | International Conference on Network and Service Management |
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Abbreviated title | CNSM |
Country | Canada |
City | Halifax |
Period | 21/10/2019 → 25/10/2019 |
Keywords
- automated end-to-end diagnostics
- call detail record
- decision tree
- machine learning
- Mobile network monitoring
- service assurance