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Predictive Edge Caching through Deep Mining of Sequential Patterns in User Content Retrievals. (arXiv:2210.02657v1 [cs.NI])
Oct. 7, 2022, 1:11 a.m. | Chen Li, Xiaoyu Wang, Tongyu Zong, Houwei Cao, Yong Liu
cs.LG updates on arXiv.org arxiv.org
Edge caching plays an increasingly important role in boosting user content
retrieval performance while reducing redundant network traffic. The
effectiveness of caching ultimately hinges on the accuracy of predicting
content popularity in the near future. However, at the network edge, content
popularity can be extremely dynamic due to diverse user content retrieval
behaviors and the low-degree of user multiplexing. It's challenging for the
traditional reactive caching systems to keep up with the dynamic content
popularity patterns. In this paper, we …
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