Abstract
Partition-based caching is emerging as an appealing solution to improve the performance of the content caching by increasing the content diversity at the network edge. In this paper, we model and analyze a vehicular network where the vehicles can obtain the requested contents from the roadside units (RSUs) by adopting the random linear network coding in the partition-based caching scheme. Specifically, the geographic distribution of the roads and RSUs are modeled by the stochastic geometry tools. The required content can be obtained from the multiple nearest RSUs and the content can be decoded by using the successive interference cancellation approach. We derive the distance distribution between the typical vehicle and the nearest RSUs, and obtain the analytical expression of the successful transmission probability of the content caching. The numerical simulations verify the analytical results and provide the guidelines for the application of the partition-based caching in vehicular networks.
This work was supported in part by the National Natural Science Foundation of China (No. 61701168, 61832005), the China Postdoctoral Science Funded Project(No. 2019M651672).
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Zhou, S., Wu, W., Tan, G. (2022). Performance Analysis of Partition-Based Caching in Vehicular Networks. In: Wang, L., Segal, M., Chen, J., Qiu, T. (eds) Wireless Algorithms, Systems, and Applications. WASA 2022. Lecture Notes in Computer Science, vol 13473. Springer, Cham. https://doi.org/10.1007/978-3-031-19211-1_26
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DOI: https://doi.org/10.1007/978-3-031-19211-1_26
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