基于数据包分析的流媒体多语义流行度模型  

Multi-semantic popularity model of streaming media based on data packet analysis

作　　者：邢玲[1] 马强[1] 余超[1] 

机构地区：[1]西南科技大学信息工程学院,四川绵阳621010

出　　处：《计算机应用研究》2012年第9期3372-3375,共4页Application Research of Computers

基　　金：国家自然科学基金资助项目(60902021;60932005;61171109)

摘　　要：流媒体技术和应用的迅猛发展,给网络带宽和系统资源带来了巨大的压力,网络信息的语义深度挖掘和兴趣偏好分析变得越来越重要。提出exUCL网络语义描述模型用于描述网络各层中数据的语义信息,通过对网络节点数据包的分析建立多语义的流媒体资源流行度模型,并采用卡方检验法和真实网络数据验证模型的有效性。该模型对提高流媒体资源的缓存替换算法效率、服务质量等均具有明显作用。With the rapid development of streaming media technology and application,there are many pressures for network bandwidth and system resources,and it becomes more and more important for the semantic mining of network information and the analysis of interest preference.So this paper used extend uniform content locator（exUCL） model to describe the semantic information in each layer of the network protocol.According to the data packet analysis of streaming media,it established the multi-semantic popularity model,and the same time it was verified with Chi-square method and real network data.This model has obvious effect in improving the efficiency of cache replacement algorithm of media resources,and the quality of customer service in streaming media system

关 键 词：流行度 多语义 数据包 统一内容定位 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]