UAV-Assisted Caching Strategy Based on Content Cache Pricing in Vehicular Networks
Abstract
:1. Introduction
2. Related Work
3. System Model
3.1. Traffic Model
3.2. Content Request Model
3.3. Caching Model and Content Delivery Strategy
3.4. Communication Model and Latency Analysis
3.5. Price Model
4. RSU Caching Strategy Considering Content Cache Pricing
4.1. Stackelberg Game for Joint Pricing and Cache Decision Optimization
4.1.1. Utility Function
4.1.2. Stackelberg Game Model
4.1.3. Iterative-Based Dynamic Programming Algorithm
Algorithm 1: Dynamic programming algorithm |
1. |
2. For to do: |
3. For to do: |
4. |
5. end for |
6. end for |
7. For to do: |
8. For to do: |
9. For to do: |
10. Calculate according to Equation (25) |
11. If : |
12. |
13. If |
14. Else if |
15. Else if |
16. Else: |
17. End if |
18. Else if : |
19. If : |
20. |
21. Else: |
22. |
23. End if |
24. Else if : |
25. If : |
26. |
27. Else: |
28. |
29. End if |
30. Else: |
31. |
32. End if |
33. End for |
34. End for |
35. End for |
36. ; |
Algorithm 2: Iterative-based dynamic programming algorithm |
1. 2. While 3. Calculate the maximum utility of NO when the lease price is by Algorithm 1. 4. Calculate the maximum utility of CP when the lease price is according to Equation (26). 5. 6. The lease price that maximizes is the final lease price 7. The utility of NO is and the cache decision is . |
4.2. Trajectory Optimization of UAV
Algorithm 3: Dijkstra-based path planning algorithm |
1. 2. For to : 3. For to : 4. 5. end for 6. end for 7. 8. While Presence of untagged nodes. 9. For in : 10. 11. If 12. 13. End if 14. end for 15. Select the closest point to the starting point from the unmarked points, denoted as 16. , add to the trajectory of the UAV |
5. Analysis of Simulation Results
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Parameter | Value |
---|---|
The number of contents | 50 |
Cache capacity of RSU | 10 |
Cache capacity of UAV | 5 |
The parameter of Zipf distribution | 0.7 |
The transmission power of RSU (mW) | 2000 |
The transmission power of UAV (mW) | 200 |
The communication radius of RSU (m) | 300 |
The communication radius of UAV (m) | 100 |
The length of lane (m) | 600 |
The fee paid by the vehicle user | 1 |
0.9 | |
0.5 |
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Gong, T.; Zhu, Q. UAV-Assisted Caching Strategy Based on Content Cache Pricing in Vehicular Networks. Appl. Sci. 2023, 13, 9246. https://doi.org/10.3390/app13169246
Gong T, Zhu Q. UAV-Assisted Caching Strategy Based on Content Cache Pricing in Vehicular Networks. Applied Sciences. 2023; 13(16):9246. https://doi.org/10.3390/app13169246
Chicago/Turabian StyleGong, Ting, and Qi Zhu. 2023. "UAV-Assisted Caching Strategy Based on Content Cache Pricing in Vehicular Networks" Applied Sciences 13, no. 16: 9246. https://doi.org/10.3390/app13169246
APA StyleGong, T., & Zhu, Q. (2023). UAV-Assisted Caching Strategy Based on Content Cache Pricing in Vehicular Networks. Applied Sciences, 13(16), 9246. https://doi.org/10.3390/app13169246