Name
Abstract | ||
|---|---|---|
Anomaly detection is important for time-critical Internet of Things (IoT) applications, such as healthcare and emergency management. The recent introduction of Fog computing architecture provides an efficient platform for delay sensitive IoT applications. Exploiting the advantages of Fog computing for anomaly detection provides the ability to detect abnormal patterns in an accurate and timely mann... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/JIOT.2017.2709942 | IEEE Internet of Things Journal |
Keywords | Field | DocType |
Cloud computing,Edge computing,Ellipsoids,Internet of Things,Computer architecture,Clustering algorithms,Data models | Edge computing,Anomaly detection,Data modeling,Computer science,Computer security,Latency (engineering),Internet of Things,Computer network,Cluster analysis,Energy consumption,Cloud computing,Distributed computing | Journal |
Volume | Issue | ISSN |
4 | 5 | 2327-4662 |
Citations | PageRank | References |
10 | 0.50 | 12 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lingjuan Lyu | 1 | 33 | 4.61 |
| Jiong Jin | 2 | 511 | 46.66 |
| Sutharshan Rajasegarar | 3 | 654 | 40.38 |
| Xuanli He | 4 | 28 | 5.81 |
| M. Palaniswami | 5 | 4107 | 290.84 |