Online Learning Algorithms for Context-Aware Video Caching in D2D Edge Networks

With the emergence of various short video platforms such as TikTok and Instagram, coupled with the accelerated pace of people's lives, people are spending more time sharing and watching online videos than ever before, and they gradually turn their attention to short videos with short duration a...

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Vydané v:	IEEE transactions on parallel and distributed systems Ročník 35; číslo 1; s. 1 - 18
Hlavní autori:	Xia, Qiufen, Jiao, Zhiwei, Xu, Zichuan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.01.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms Approximation Approximation algorithm Approximation algorithms Caching Confidence intervals Context context-aware video caching D2D edge network Delay Delays Device-to-device communication Distance learning Edge computing Electronic devices Energy budget Energy consumption Energy levels Energy storage Machine learning Mathematical analysis Mobile handsets Network latency Prediction algorithms Quality of service Storage capacity Uncertainty User requirements Video
ISSN:	1045-9219, 1558-2183
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