摘要
在线视频服务用户选择服务质量最佳的视频服务提供商,其存在的主要问题是来自于用户网络的异构性和动态性。为此,基于海服务架构,设计并实现一个面向在线视频服务的测量和推荐系统。模拟大量用户端节点进行测量,并根据测量结果预测用户的体验质量,据此向用户提供实时服务源推荐。运用该系统构建一个包含10家视频网站的视频测量和推荐系统,观测9个月的数据并进行分析。实验结果表明,该测量与推荐系统可以向用户提供服务源推荐,使用户获得当前网络状况下对该视频内容最佳的观看体验。
Selecting the proper service provider for different users has many important problems.The most important one comes from the heterogeneity and dynamic of user's network.Therefore,based on the sea service architecture,a measurement and recommendation system oriented online video services is designed and implemented.The system simulates a large number of client nodes to measure and predict the user's Quality of Experience(QoE)based on the measurement results,thereby providing users with real-time service source recommendations.The system is used to build a video measurement and recommendation system containing 10 video sites,and the data for 9 months are observed and analyzed.Experimental results show that the system can provide service source recommendation to users needs to watch,so that the user can use the system to obtain the best viewing experience under the current network conditions.
作者
卓煜
尤佳莉
王劲林
齐卫宁
乔楠楠
ZHUO Yu;YOU Jiali;WANG Jinlin;QI Weining;QIAO Nannan(National Network New Media Engineering Research Center,Institute of Acoustics,Chinese Academy of Sciences,Beijing 100190,China;University of Chinese Academy of Sciences,Beijing 100190,China)
出处
《计算机工程》
CAS
CSCD
北大核心
2018年第4期28-34,40,共8页
Computer Engineering
基金
中国科学院战略性先导科技专项"智能电视平台与服务支撑环境研制"(XDA06040501)
关键词
在线视频服务
海服务
网络测量
视频质量
服务推荐
大数据
online video service
sea service
network measurement
video quality
service recommendation
big data
