QoE-based video segments caching strategy in urban public transportation system  

作　　者：Wang Hang Li Xi Ji Hong Zhang Heli 

机构地区：[1]School of Telecommunication Engineering,Beijing University of Posts and Telecommunications,Beijing 100876,China

出　　处：《The Journal of China Universities of Posts and Telecommunications》2021年第4期29-38,共10页中国邮电高校学报（英文版）

基　　金：supported by the National Natural Science Foundation of China(61771070)。

摘　　要：With the rapid development of vehicle-based applications, entertainment videos have gained popularity for passengers on public vehicles. Therefore, how to provide high quality video service for passengers in typical public transportation scenarios is an essential problem. This paper proposes a quality of experience(QoE)-based video segments caching(QoE-VSC) strategy to guarantee the smooth watching experience of passengers. Consequently, this paper considers a jointly caching scenario where the bus provides the beginning segments of a video, and the road side unit(RSU) offers the remaining for passengers. To evaluate the effectiveness, QoE hit ratio is defined to represent the probability that the bus and RSUs jointly provide passengers with desirable video segments successfully. Furthermore, since passenger volume change will lead to different video preferences, a deep reinforcement learning(DRL) network is trained to generate the segment replacing policy on the video segments cached by the bus server. And the training target of DRL is to maximize the QoE hit ratio, thus enabling more passengers to get the required video. The simulation results prove that the proposed method has a better performance than baseline methods in terms of QoE hit ratio and cache costs.

关 键 词：caching strategy quality of experience deep reinforcement learning urban public transportation system 

分 类 号：TN919.8[电子电信—通信与信息系统] U495[电子电信—信息与通信工程]