Content-Caching-Oriented Popularity Forecast and User Clustering

Content popularity forecast is a key enabler toward the realization of proactive content caching, contributing to significant reduction of content fetching delay. Different from most of the existing literature that concentrating on enhancing the forecast accuracy, we tailor the popularity forecast a...

Full description

Saved in:

Bibliographic Details
Published in:	IEEE internet of things journal Vol. 11; no. 23; pp. 38425 - 38440
Main Authors:	Wang, Yitu, Chen, Qi, Wang, Wei, Nakachi, Takayuki, Zhang, Guangchen, Liou, Juinjei
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 01.12.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Accuracy Algorithms Caching Clustering Clustering algorithms Complexity theory content caching Gaussian process Gaussian process (GP) Iterative algorithms K-means popularity forecast Prediction algorithms Predictive models Servers Time series analysis
ISSN:	2327-4662, 2327-4662
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!