Research on Optimization of Cloud Computing Resource Allocation Strategy in Scenic Area Operation and Management under Smart Tourism
24 set 2025
INFORMAZIONI SU QUESTO ARTICOLO
Pubblicato online: 24 set 2025
Ricevuto: 28 dic 2024
Accettato: 17 apr 2025
DOI: https://doi.org/10.2478/amns-2025-0976
Parole chiave
© 2025 Yanlong Wang, published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
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Relative standard deviation
| Resource nodes | FOA-ACA | GA | ACO |
|---|---|---|---|
| 20 | 0.54 | 0.73 | 0.57 |
| 40 | 0.33 | 0.54 | 0.43 |
| 60 | 0.22 | 0.42 | 0.38 |
| 80 | 0.17 | 0.3 | 0.19 |
| 100 | 0.12 | 0.21 | 0.15 |
Test parameter selection
| Parameter | Numerical value | Parameter | Numerical value |
|---|---|---|---|
| Volatile factor | 0.65 | Population scale | 60 |
| Pheromones strengthening factor | 0.45 | Mutation rate | 0.06 |
| pheromones factor | 1.2 | Cross rate | 0.45 |
| Pheromone Inspiration factor | 3 | Minimum evolutionary rate | 0.06 |
| Expected value | 1.2 | Maximum iteration algebra | 550 |
| q0 | 0.8 |
