Name
Abstract | ||
|---|---|---|
We have proposed a self-diagnosis algorithm using causal graph modeling to perform distributed diagnosis for a VoIP service in IMS network. Our solution achieves a global self-diagnosis process based on local knowledge of each network element. We implement this approach in an IMS platform and detail the corresponding causal graph and diagnosis process. The results of the implementation verify that our approach is effective and could be used to identify the primary cause of the alarm. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/CyberC.2015.92 | CyberC |
Keywords | Field | DocType |
self-diagnosis, causal graph, VoIP service, IMS network, distributed algorithm | Graph,Self-diagnosis,Computer science,ALARM,Computer network,Algorithm,Distributed algorithm,Knowledge extraction,Network element,Voice over IP,Distributed computing | Conference |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jingxian Lu | 1 | 3 | 0.90 |
| Christophe Dousson | 2 | 0 | 0.34 |
| francine krief | 3 | 121 | 26.99 |