“Caching with Recommendation and Reinforcement Learning” in Edge Caching for Mobile Networks
Author：Liu Dong Time：January 10, 2022 Number of clicks：
Caching enables the storage of Internet-based content, including web objects, videos and software updates. When web objects are downloaded from the Internet or across wide-area-network (WAN) links, edge caching stores them at the edge of the network. Content can also be proactively cached at the edge based on its predicted popularity. When subsequent requests come for cached material, the content is quickly delivered from edge caching, without the need to download the data again over the WAN. The result is the ability to help save bandwidth, particularly at times of peak network load, increase content delivery, and provide users with a faster and better network experience.
In this comprehensive edited book, the editors and authors introduce edge caching in mobile networks from a fundamental perspective and discuss its role in saving bandwidth and reducing latency over wireless channels. Many physical layer models and techniques, including interference alignment and beamforming are considered, as well as recent advances on intelligent and proactive communication systems capable of recommending content to users to improve quality of experience and spectral efficiency.
The book provides systematic and thorough coverage of edge caching for mobile networks for an audience of researchers, engineers and scientists from academia and industry working in the fields of information and communication technology, data science and AI.
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