Name
Abstract | ||
|---|---|---|
•An GAN-based method for time-dependent cloud workload generation is proposed.•The method does not rely on any prior knowledge to capture the data distribution.•Spectral normalization is used to stabilize the adversarial training.•Achieving better results than state-of-art models.•Enabled conditional workload generation with simple changes on models. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.jpdc.2022.05.007 | Journal of Parallel and Distributed Computing |
Keywords | DocType | Volume |
Cloud computing,Time-dependent workload generation,Generative adversarial networks,Deep learning | Journal | 168 |
ISSN | Citations | PageRank |
0743-7315 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Weiwei Lin | 1 | 147 | 13.95 |
| Kun Yao | 2 | 0 | 0.34 |
| Lan Zeng | 3 | 0 | 0.34 |
| Fagui Liu | 4 | 23 | 6.06 |
| Chun Shan | 5 | 3 | 2.42 |
| Xiaobin Hong | 6 | 4 | 2.55 |