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Online Caching Policy with User Preferences and Time-Dependent Requests: A Reinforcement Learning Approach
Univ Oulu, Finland.
Univ Oulu, Finland.
Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
2019 (English)In: CONFERENCE RECORD OF THE 2019 FIFTY-THIRD ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS, IEEE , 2019, p. 1384-1388Conference paper, Published paper (Refereed)
Abstract [en]

Content caching is a promising approach to reduce data traffic in the back-haul links. We consider a system where multiple users request items from a cache-enabled base station that is connected to a cloud. The users request items according to the user preferences in a time-dependent fashion, i.e., a user is likely to request the next chunk (item) of the file requested at a previous time slot. Whenever the requested item is not in the cache, the base station downloads it from the cloud and forwards it to the user. In the meanwhile, the base station decides whether to replace one item in the cache by the fetched item, or to discard it. We model the problem as a Markov decision process (MDP) and propose a novel state space that takes advantage of the dynamics of the users requests. We use reinforcement learning and propose a Q-learning algorithm to find an optimal cache replacement policy that maximizes the cache hit ratio without knowing the popularity profile distribution, probability distribution of items, and user preference model. Simulation results show that the proposed algorithm improves the cache hit ratio compared to other baseline policies.

Place, publisher, year, edition, pages
IEEE , 2019. p. 1384-1388
Series
Conference Record of the Asilomar Conference on Signals Systems and Computers, ISSN 1058-6393
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:liu:diva-168234DOI: 10.1109/IEEECONF44664.2019.9048832ISI: 000544249200265ISBN: 978-1-7281-4300-2 (electronic)OAI: oai:DiVA.org:liu-168234DiVA, id: diva2:1459408
Conference
53rd Asilomar Conference on Signals, Systems, and Computers
Note

Funding Agencies|Infotech Oulu; Academy of FinlandAcademy of Finland [323698]; Academy of Finland 6Genesis Flagship [318927]; European Unions Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie GrantEuropean Union (EU) [793402]

Available from: 2020-08-19 Created: 2020-08-19 Last updated: 2020-08-19

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf