Name
Abstract | ||
|---|---|---|
The Self-Organizing Networks (SON) concept includes the functional area known as self-healing, which aims to automate the detection and diagnosis of, and recovery from, network degradations and outages. Changes to the configuration management (CM) parameters for network elements could be a cause for degraded network performance and stability; hence, the verification of their effects becomes crucial. In this paper, we present SONVer, a tool that performs SON verification, using anomaly detection and diagnosis techniques that operate within a specified spatial scope larger than an individual cell. SONVer automatically classifies the state of the network in the presence of CM changes, indicating the root cause for anomalous conditions. SONVer uses Key Performance Indicators (KPIs) and CM history from real cellular networks to determine the state of the network; visualize anomalies at a large scale; and identify the causes of anomalies and the group of cells that were affected. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ISWCS.2014.6933426 | Wireless Communications Systems |
Keywords | Field | DocType |
cellular radio,configuration management,telecommunication network management,telecommunication network reliability,SON verification,SONVer,configuration management parameters,key performance indicators,network elements,network performance,network stability,network state classification,operational cellular networks,self-healing networks,self-organizing networks,SON verification,anomaly detection,diagnosis,network automation,self-organized networks (SON) | Anomaly detection,Computer science,Computer network,Network architecture,Network simulation,Real-time computing,Self-organizing network,Network management application,Intelligent computer network,Network performance,Network management station | Conference |
Citations | PageRank | References |
1 | 0.35 | 1 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ciocarlie, G.F. | 1 | 1 | 0.35 |
| Chih-Chieh Cheng | 2 | 7 | 0.90 |
| Connolly, C. | 3 | 7 | 0.90 |
| Lindqvist, U. | 4 | 18 | 2.29 |