Coping with Mobile Backhaul Bandwidth Limitation: User Clustering and Content Sharing
Zhiwei Zhang
Department of Automation, University of Science and Technology of China, Hefei 230027, China.
Qiang Ling *
Department of Automation, University of Science and Technology of China, Hefei 230027, China.
Lixiang Xu
Department of Automation, University of Science and Technology of China, Hefei 230027, China.
Feng Li
Department of Automation, University of Science and Technology of China, Hefei 230027, China.
Song Wang
Department of Automation, University of Science and Technology of China, Hefei 230027, China.
*Author to whom correspondence should be addressed.
Abstract
With the development of 4G mobile communication technologies, mobile networks are evolving into a new generation, which is expected to support not only the traditional services such as phone calls and text messages, but also the high-speed applications such as real-time videos, streaming music. Mobile networks are composed of Mobile Core Networks and Mobile Access Networks. Advances in wireless communication technologies have shifted the data traffic bottleneck to the mobile core network, which is either too expensive or too complex to upgrade. Caching technology is considered as a promising and economic technology to cope with this problem. In this paper, we propose a new caching architecture in which the cached contents in user mobile devices are shared among users with similar media content preference over the eNode in the Radio Access Network, thus decreasing the data traffic going through the Mobile Core Network. In order to make the best use of mobile devices' cache space, a centralized cache management algorithm, which is expected to run at the base station and control the cache objects in user mobile devices, is also designed Simulation shows that via cache content sharing among users with similar content preference, great cache performance gain can be achieved in terms of saving backhaul bandwidth and reducing the average user request delay.
Keywords: Mobile terminal cache, user preference, user clustering, content sharing.