期刊
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
卷 91, 期 -, 页码 590-600出版社
ELSEVIER
DOI: 10.1016/j.future.2018.08.019
关键词
Information centric networking; Edge caching; Location prediction; User interest; Content popularity
资金
- Hunan Science and Technology Plan, China [2012RS4054]
- Natural Science Foundation of China [61672535, 61472005]
- Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education Innovation Fund, China [JYB201502]
- Key Laboratory of Information Processing and Intelligent Control of Fujian Innovation Fund, China [MJUKF201735]
- Natural Science Foundation of Hunan Province, China [2018JJ3203]
- Graduate Student Innovation Project of Hunan, China [CX2016B049]
- Research Foundation of Education Bureau of Hunan Province, China [17C0679]
- Hunan University of Science and Engineering Research Project, China [17XKY071]
- key discipline for computer application and technology of Hunan University of Science and Engineering, China
The widespread applications of mobile multimedia are causing the demands of the users on the network to be increasingly prominent. Edge computing enables the deployment of services, applications, content storage, and processing in close proximity to mobile end users. By fully exploiting its advantages, we propose the edge Internet of Things equipment-assisted caching multimedia for information centric networking for improving the user experience. To achieve this, we propose the location prediction method and smart caching strategy based on machine learning to predict the user interest in this paper. This will drive the user interest content from the server to the edge node. Moreover, we propose an optimized caching replacement algorithm for improving the cache utilization. The experimental results reveal that the proposed architecture and strategy are efficient for caching mobile multimedia content, which can optimize the hit ratio and reduce the access time in comparison with other existing solutions. (C) 2018 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据