Tehnički vjesnik, Vol. 26 No. 2, 2019.
Izvorni znanstveni članak
https://doi.org/10.17559/TV-20190303092125
Cooperative Caching with Content Popularity Prediction for Mobile Edge Caching
Sanshan Sun
; National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu, China
Wei Jiang
orcid.org/0000-0003-2962-4709
; National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu, China
Gang Feng
; National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu, China
Shuang Qin
; National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu, China
Ye Yuan
; School of Economics and Management, Chongqing University of Posts and Telecommunications, Chongqing, China
Sažetak
Mobile Edge Caching (MEC) can be exploited for reducing redundant data transmissions and improving content delivery performance in mobile networks. However, under the MEC architecture, dynamic user preference is challenging the delivery efficiency due to the imperfect match between users' demands and cached content. In this paper, we propose a learning-based cooperative content caching policy to predict the content popularity and cache the desired content proactively. We formulate the optimal cooperative content caching problem as a 0-1 integer programming for minimizing the average downloading latency. After using an artificial neural network to learn content popularity, we use a greedy algorithm for its approximate solution. Numerical results validate that the proposed policy can significantly increase content cache hit rate and reduce content delivery latency when compared with popular caching strategies.
Ključne riječi
caching; cooperative; mobile edge caching; neural network
Hrčak ID:
219543
URI
Datum izdavanja:
24.4.2019.
Posjeta: 1.584 *