Content Fetching Delay Optimization-Based Caching and Resource Allocation for UAV-Enabled Networks

In this work, we investigate content caching problem in unmanned aerial vehicle (UAV)-enabled networks where UAVs are allowed to store user requested content so as to enhance the content transmission performance of users. To predict user content request, we propose a bidirectional long short-term me...

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Vydáno v:IEEE access Ročník 12; s. 62429 - 62447
Hlavní autoři: Bayessa, Gezahegn Abdissa, Chai, Rong, Liang, Chengchao, Diallo, Elhadj Moustapha, Chen, Qianbin
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Autonomous aerial vehicles
Bayes methods
Caching
Clustering
Clustering methods
content caching
Delay
Delays
Logic gates
Long short term memory
Prediction algorithms
Resource allocation
Resource management
Subcarriers
UAV deployment
Unmanned aerial vehicles
user clustering
ISSN:2169-3536, 2169-3536
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Shrnutí:In this work, we investigate content caching problem in unmanned aerial vehicle (UAV)-enabled networks where UAVs are allowed to store user requested content so as to enhance the content transmission performance of users. To predict user content request, we propose a bidirectional long short-term memory-based algorithm. Then, the content transmission delay of users is examined and the UAV deployment, content caching and resource allocation problem is formulated as an overall content fetching delay minimization problem. As the formulated problem is difficult to solve, we transform it into two subproblems which are solved iteratively. To tackle the UAV deployment and content caching subproblem, we first design a modified K-means-based clustering scheme and then propose a UAV deployment strategy by using quadratic transformation. To solve subcarrier and power allocation subproblem, we apply Lagrangian dual method to determine power allocation strategy and propose a Kuhn-Munkres algorithm-based subcarrier allocation strategy. Simulation results demonstrate the effectiveness of the proposed algorithms.
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2024.3395279