6533b828fe1ef96bd1287a41
RESEARCH PRODUCT
Cognitive self-healing system for future mobile networks
Fedor ChernogorovJanne KurjenniemiVilho RäisänenIlmari RepoTimo Nihtilasubject
ta113cognitionta213Performance managementComputer sciencebusiness.industryDistributed computingCognitiondata miningcomputer.software_genreAutomationanomaly detectionFault detection and isolation5G networksNetwork simulationcompensationcell outageRobustness (computer science)self-healingAnomaly detectionData miningbusinesscomputer5Gdescription
This paper introduces a framework and implementation of a cognitive self-healing system for fault detection and compensation in future mobile networks. Performance monitoring for failure identification is based on anomaly analysis, which is a combination of the nearest neighbor anomaly scoring and statistical profiling. Case-based reasoning algorithm is used for cognitive self-healing of the detected faulty cells. Validation environment is Long Term Evolution (LTE) mobile system simulated with Network Simulator 3 (ns-3) [1, 2]. Results demonstrate that cognitive approach is efficient for compensation of cell outages and is capable to improve network coverage. Anomaly analysis can be used for identification of network failures, and automation of performance management. Introduction of data mining and cognition to the future mobile networks, e.g. 5th Generation (5G), is especially important as it allows to meet the strict requirements for robustness and enhanced performance.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2015-08-01 | 2015 International Wireless Communications and Mobile Computing Conference (IWCMC) |