A group intelligence optimisation method for privacy protection problems in smart home environments
Feb 03, 2025
About this article
Published Online: Feb 03, 2025
Received: Oct 04, 2024
Accepted: Jan 02, 2025
DOI: https://doi.org/10.2478/amns-2025-0028
Keywords
© 2025 Jiaze Yu, published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
Figure 1.
Figure 2.
Figure 3.
Energy consumption contrast
| ACA | FVR | ||
|---|---|---|---|
| System1 | System2 | Difference value | |
| 0.1 | 29.98 | 17.93 | 12.05 |
| 0.2 | 22.17 | 12.26 | 9.91 |
| 0.3 | 18.54 | 9.88 | 8.66 |
| 0.4 | 13.92 | 6.57 | 7.35 |
| 0.5 | 10.05 | 3.85 | 6.2 |
| 0.6 | 8.54 | 2.51 | 6.03 |
| 0.7 | 6.18 | 2.12 | 4.06 |
| 0.8 | 4.23 | 1.57 | 2.66 |
| 0.9 | 2.93 | 0.88 | 2.05 |
Computational overhead
| Method | User(ms) | Server(ms) | Registration center(ms) | Total cost(ms) |
|---|---|---|---|---|
| Logistic | 0.076 | 0.044 | - | 0.119 |
| FPGA | 25.086 | 32.199 | - | 57.285 |
| LoRa | 0.075 | 0.058 | 0.150 | 0.283 |
| OFDM | 10.497 | 10.462 | - | 20.959 |
| ECC | 0.090 | 0.064 | 0.149 | 0.303 |
| ZYNQ | 12.727 | 12.951 | - | 25.678 |
| M-LVDS | 0.086 | 0.054 | - | 0.139 |
| DSP | 0.076 | 0.037 | - | 0.113 |
| Methods of this article | 0.030 | 0.039 | - | 0.068 |