Turkish Journal of Electrical Engineering and Computer Sciences
Abstract
The Unmanned Aerial Vehicle (UAV) can be used as good flying base stations to cache popular content and follow a user mobility pattern, to help them in a suitable services. Conventional edge caching algorithms often prioritize cache contents with higher popularity. Nevertheless, the cache capacity of mobile devices is restricted, and diverse clients may have expansive varieties in content inclination designs. In this manner, the performance and effectiveness of the cache will be so constrained without great strategies. The composition of recommender system and edge caching is considered as a new research topic, which is used to reduce cost and improve the cache hit ratio. We examine a network containing of a UAV as a fog node in this paper. Considering that caching the appropriate content in the UAV has a great effect on increasing the hit rate and reducing the response time for the user, we use the content-based recommender system method, and we determine the attribute coefficients considered in the recommender system in a more efficient way with the feature importance method. Also, we study three methods for content-based recommendation to compare results with the common methods of Most Popular Contents (MPC) and Uniform Distributed Caching (UDC). The first and third methods have better results than the common methods of MPC and UDC. Finally, we propose two methods that are a hybrid of the methods described in this paper. The proposed method is better than the previous methods described in this paper, with a value of about 0.01 for songs dataset and about 0.03 for MovieLens dataset. It is possible to customize similarity according to the dataset. Also, since response time is really important in UAV, the run time is low compared to artificial intelligence methods.
DOI
10.55730/1300-0632.4113
Keywords
Unmanned Aerial Vehicle (UAV), Caching, Recommender system, Content-based recommendation, Fog computing
First Page
48
Last Page
64
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
DARBANIAN, ELHAM and NICKRAY, MOHSEN
(2025)
"A content-based recommender system for the UAV caching in the field of entertainment in fog computing,"
Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 33:
No.
1, Article 5.
https://doi.org/10.55730/1300-0632.4113
Available at:
https://journals.tubitak.gov.tr/elektrik/vol33/iss1/5
Included in
Computer Engineering Commons, Computer Sciences Commons, Electrical and Computer Engineering Commons
