Reference : Active Popularity Learning with Cache Hit Ratio Guarantees using a Matrix Completion ...

	Document type :	Scientific congresses, symposiums and conference proceedings : Unpublished conference
	Discipline(s) :	Engineering, computing & technology : Multidisciplinary, general & others
	Focus Areas :	Security, Reliability and Trust
	To cite this reference:	http://hdl.handle.net/10993/45176

Title :	Active Popularity Learning with Cache Hit Ratio Guarantees using a Matrix Completion Committee
Language :	English
Translated title :	[en] Active Popularity Learning with Cache Hit Ratio Guarantees using a Matrix Completion Committee
Author, co-author :	Bommaraveni, Srikanth [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
	Vu, Thang Xuan [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
	Chatzinotas, Symeon [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
	Ottersten, Björn [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Publication date :	8-Oct-2020
Number of pages :	5
Peer reviewed :	Yes
On invitation :	No
Audience :	International
Event name :	2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications
Event date :	31-8-2020 to 3-9-2020
Keywords :	[en] Edge caching ; Active learning ; Matrix completion
Abstract :	[en] Edge caching is a promising technology to facethe stringent latency requirements and back-haul trafficoverloading in 5G wireless networks. However, acquiringthe contents and modeling the optimal cache strategy is achallenging task. In this work, we use an active learningapproach to learn the content popularities since it allowsthe system to leverage the trade-off between explorationand exploitation. Exploration refers to caching new fileswhereas exploitation use known files to cache, to achievea good cache hit ratio. In this paper, we mainly focus tolearn popularities as fast as possible while guaranteeing anoperational cache hit ratio constraint. The effectiveness ofproposed learning and caching policies are demonstratedvia simulation results as a function of variance, cache hitratio and used storage.
Research centres :	Interdisciplinary Centre for Security, Reliability and Trust (SnT) > SIGCOM
Funders :	National Re-search Fund
Name of the research project :	LARGOS
Target :	Researchers ; Professionals ; Students ; General public
Permalink :	http://hdl.handle.net/10993/45176
DOI :	10.1109/PIMRC48278.2020.9217322
FnR project :	FnR

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