Echo State Network-Based Content Prediction for Mobile Edge Caching Networks

Zengyu Cai, Xi Chen, Jianwei Zhang, Liang Zhu and Xinhua Hu
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Zengyu Cai: Zhengzhou University of Light Industry, China
Xi Chen: Zhengzhou University of Light Industry, China
Jianwei Zhang: Zhengzhou University of Light Industry, China
Liang Zhu: Zhengzhou University of Light Industry, China
Xinhua Hu: Zhengzhou University of Light Industry, China

International Journal of Information Technology and Web Engineering (IJITWE), 2023, vol. 18, issue 1, 1-16

Abstract: With the rapid development of internet communication and the wide application of intelligent terminal, moving the cache to the edge of the network is an effective solution to shorten the delay of users accessing content. However, the existing cache work lacks the comprehensive consideration of users and content, resulting in low cache hit ratio and low accuracy of the whole system. In this paper, the authors propose a collaborative caching model that considers both user request content and content prediction, so as to improve the caching performance of the whole network. Firstly, the model uses the clustering algorithm based on Akike information criterion to cluster users. Then, combined with the clustering results, echo state network is used as the machine learning framework to predict the content. Finally, the cache contents are selected according to the prediction results and cached in the cache unit of the small base station. Simulation results show that compared with the existing cache algorithms, the proposed method has obvious improvement in cache hit ratio, accuracy, and recall rate.

Date: 2023
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