Advances, Systems and Applications
From: VTGAN: hybrid generative adversarial networks for cloud workload prediction
Method | Window size | Train:Test ratio | MAPE |
---|---|---|---|
Bi-LSTM [44] | Â | 65:35 | 12.0119 |
 |  | 70:30 | 12.2173 |
 | 30 | 75:25 | 12.3019 |
 |  | 80:20 | 13.6177 |
 |  | 65:35 | 11.7046 |
 |  | 70:30 | 11.7091 |
 | 60 | 75:25 | 11.914 |
 |  | 80:20 | 13.6163 |
 |  | 65:35 | 12.0244 |
 |  | 70:30 | 12.3091 |
 | 90 | 75:25 | 12.8671 |
 |  | 80:20 | 13.1198 |
 |  | 65:35 | 12.0802 |
 |  | 70:30 | 11.8903 |
 | 120 | 75:25 | 14.207 |
 |  | 80:20 | 13.4428 |
BHyPreC [44] | Â | 65:35 | 11.1799 |
 |  | 70:30 | 12.3343 |
 | 30 | 75:25 | 12.3688 |
 |  | 80:20 | 12.2959 |
 |  | 65:35 | 11.1101 |
 |  | 70:30 | 13.0751 |
 | 60 | 75:25 | 11.7641 |
 |  | 80:20 | 13.507 |
 |  | 65:35 | 12.537 |
 |  | 70:30 | 12.2912 |
 | 90 | 75:25 | 10.8557 |
 |  | 80:20 | 12.4713 |
 |  | 65:35 | 12.2044 |
 |  | 70:30 | 10.7738 |
 | 120 | 75:25 | 12.706 |
 |  | 80:20 | 13.3193 |
VTGAN (LSTM-based) | Â | 65:35 | 10.5822 |
 |  | 70:30 | 9.47898 |
 | 30 | 75:25 | 9.39637 |
 |  | 80:20 | 9.0233 |
 |  | 65:35 | 10.911 |
 |  | 70:30 | 10.1507 |
 | 60 | 75:25 | 10.4705 |
 |  | 80:20 | 9.3998 |
 |  | 65:35 | 10.3466 |
 |  | 70:30 | 13.6877 |
 | 90 | 75:25 | 11.146 |
 |  | 80:20 | 11.2193 |
 |  | 65:35 | 13.0493 |
 |  | 70:30 | 14.7279 |
 | 120 | 75:25 | 12.4581 |
 |  | 80:20 | 12.8819 |
VTGAN (GRU-based) | Â | 65:35 | 8.87 |
 |  | 70:30 | 8.6018 |
 | 30 | 75:25 | 9.1799 |
 |  | 80:20 | 9.6228 |
 |  | 65:35 | 8.5347 |
 |  | 70:30 | 8.4522 |
 | 60 | 75:25 | 9.044 |
 |  | 80:20 | 8.1686 |
 |  | 65:35 | 8.747 |
 |  | 70:30 | 8.8152 |
 | 90 | 75:25 | 8.5942 |
 |  | 80:20 | 8.3724 |
 |  | 65:35 | 8.6346 |
 |  | 70:30 | 9.0875 |
 | 120 | 75:25 | 8.0545 |
 |  | 80:20 | 8.5751 |