Research Area:  Edge Computing
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.
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Author(s) Name:  Yayuan Tang,Kehua Guo,Jianhua Ma,Yutong Shen and Tao Chi
Journal name:  Future Generation Computer Systems
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Publisher name:  ELSEVIER
DOI:  10.1016/j.future.2018.08.019
Volume Information:  Volume 91, February 2019, Pages 590-600
Paper Link:   https://www.sciencedirect.com/science/article/abs/pii/S0167739X18311841