University of Oulu

S. Tamoor-ul-Hassan, S. Samarakoon, M. Bennis, M. Latva-aho and C. S. Hong, "Learning-Based Caching in Cloud-Aided Wireless Networks," in IEEE Communications Letters, vol. 22, no. 1, pp. 137-140, Jan. 2018. doi: 10.1109/LCOMM.2017.2759270

Learning-based caching in cloud-aided wireless networks

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Author: Tamoor-ul-Hassan, Syed1; Samarakoon, Sumudu1; Bennis, Mehdi1,2;
Organizations: 1Center for Wireless Communications, University of Oulu, 90014 Oulu, Finland
2Department of Computer Science and Engineering, Kyung Hee University, Seoul 02447, South Korea
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.5 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2018
Publish Date: 2019-06-05


This letter studies content caching in cloud-aided wireless networks, where small cell base stations with limited storage are connected to the cloud via limited capacity fronthaul links. By formulating a utility (inverse of service delay) maximization problem, we propose a cache update algorithm based on spatio-temporal traffic demands. To account for the large number of contents, we propose a content clustering algorithm to group similar contents. Subsequently, with the aid of regret learning at small cell base stations and the cloud, each base station caches contents based on the learned content popularity subject to its storage constraints. The performance of the proposed caching algorithm is evaluated for sparse and dense environments, while investigating the tradeoff between global and local class popularity. Simulation results show 15% and 40% gains in the proposed method compared to various baselines.

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Series: IEEE communications letters
ISSN: 1089-7798
ISSN-E: 2373-7891
ISSN-L: 1089-7798
Volume: 22
Issue: 1
Pages: 137 - 140
DOI: 10.1109/LCOMM.2017.2759270
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
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