Name
Abstract | ||
|---|---|---|
This paper proposes a novel technique to facilitate an energy-aware anomaly detection in the context of edge-cloud collaborative architecture, where anomaly-oriented attributes provided by multi-modal smart things are recognized as primary and secondary ones with respect to the characteristic of certain anomaly. Experimental results demonstrate the promising performance and efficiency of our proposed technique in reducing network traffic and energy consumption in comparison with the state of artu0027s techniques. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00180 | SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
6 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaocui Li | 1 | 3 | 2.06 |
| Zhangbing Zhou | 2 | 11 | 6.99 |
| Jine Tang | 3 | 0 | 0.34 |
| Shu Lei | 4 | 2927 | 216.78 |