Name
Title | ||
|---|---|---|
Anomaly detection and diagnosis for cloud services: Practical experiments and lessons learned. |
Abstract | ||
|---|---|---|
•Anomaly detection system (ADS) for cloud services based on machine learning algorithms.•Two diagnosis levels: anomalous VM behavior and type of error causing the anomaly.•Deployment and validation of the ADS on a VMware based cloud-computing platform.•Generation of complete datasets for training and validation using error emulation.•Two case studies: MongoDB database and a virtual network function (VNF). |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.jss.2018.01.039 | Journal of Systems and Software |
Keywords | Field | DocType |
Anomaly detection,System monitoring,Machine learning,Fault injection,SLA,Diagnosis,Virtualization | Virtual network,Virtualization,Anomaly detection,Dependability,Virtual machine,Computer science,Real-time computing,NoSQL,IP Multimedia Subsystem,Cloud computing | Journal |
Volume | Issue | ISSN |
139 | C | 0164-1212 |
Citations | PageRank | References |
11 | 0.64 | 48 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Carla Sauvanaud | 1 | 53 | 3.82 |
| Mohamed Kaâniche | 2 | 483 | 62.58 |
| Karama Kanoun | 3 | 863 | 93.18 |
| Kahina Lazri | 4 | 35 | 4.94 |
| Guthemberg Silvestre | 5 | 36 | 3.68 |