Video caching and scheduling with edge cooperation  

作　　者：Zhidu Li Fuxiang Li Tong Tang Hong Zhang Jin Yang 

机构地区：[1]School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing,400065,China [2]Advanced Network and Intelligent Connection Technology Key Laboratory of Chongqing Education Commission of China,Chongqing,400065,China [3]Key Laboratory of Ubiquitous Sensing and Networking in Chongqing,Chongqing,400065,China

出　　处：《Digital Communications and Networks》2024年第2期450-460,共11页数字通信与网络（英文版）

基　　金：the National Natural Science Foundation of China under grants 61901078,61871062,and U20A20157;in part by the China University Industry-University-Research Collaborative Innovation Fund(Future Network Innovation Research and Application Project)under grant 2021FNA04008;in part by the China Postdoctoral Science Foundation under grant 2022MD713692;in part by the Chongqing Postdoctoral Science Special Foundation under grant 2021XM2018;in part by the Natural Science Foundation of Chongqing under grant cstc2020jcyj-zdxmX0024;in part by University Innovation Research Group of Chongqing under grant CXQT20017;in part by the Science and Technology Research Program of Chongqing Municipal Education Commission under Grant KJQN202000626;in part by the Youth Innovation Group Support Program of ICE Discipline of CQUPT under grant SCIE-QN-2022-04.

摘　　要：In this paper,we explore a distributed collaborative caching and computing model to support the distribution of adaptive bit rate video streaming.The aim is to reduce the average initial buffer delay and improve the quality of user experience.Considering the difference between global and local video popularities and the time-varying characteristics of video popularity,a two-stage caching scheme is proposed to push popular videos closer to users and minimize the average initial buffer delay.Based on both long-term content popularity and short-term content popularity,the proposed caching solution is decouple into the proactive cache stage and the cache update stage.In the proactive cache stage,we develop a proactive cache placement algorithm that can be executed in an off-peak period.In the cache update stage,we propose a reactive cache update algorithm to update the existing cache policy to minimize the buffer delay.Simulation results verify that the proposed caching algorithms can reduce the initial buffer delay efficiently.

关 键 词：Video service Distributed and collaborative caching Long-term popularity Short-term popularity 

分 类 号：TN91[电子电信—通信与信息系统]