Popularity-Prediction-driven Hierarchical Caching in Fog-Cloud based Radio Access Networks
Content requests from mobile users are explosively increas-ing due to the growing popularity of mobile social activities.However,current mobile network infrastructure cannot ef-fectively support the generated massive mobile data traffic while maintaining consistent and acceptable network perfor-mances.To deal with such a serious challenge,caching pop-ular content at the edges of mobile networks has been recog-nized as a promising solution.In this paper,we introduce the content caching technique in Fog-Cloud based radio access networks for offering joint Fog-enabled and Cloud-enabled data services.Then we propose a collaborative hierarchical Fog-Cloud caching framework based on predicting content popularity with the Auto Regressive model.Our objective is to explore the maximum capacity of the considered net-work infrastructure by effectively offloading network traffic.Trace-driven evaluations demonstrate the effectiveness of our proposed caching mechanism in terms of traffic offload.
Fog-Cloud Computing edge caching traffic offloading pop-ularity prediction
Xiuhua Li Xiaofei Wang Zhengguo Sheng Chunqiang Hu Victor C.M.Leung
School of Big Data&Software Engineering,Chongqing University,Chongqing,China School of Computer Science and Technology,Tianjin University,Tianjin,China Dept.of Engineering and Design,University of Sussex,Falmer Brighton,United Kingdom Dept.Electrical and Computer Engineering,The University of British Columbia,Vancouver,Canada
国际会议
2019国图灵大会(ACM Turing Celebration conference-China 2019 )
成都
英文
365-370
2019-05-17（万方平台首次上网日期，不代表论文的发表时间）