Cache replacement strategy for streaming media based on semantic mining

Ling Xing, Jianguo Ma, Hong Cheng
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Abstract

In order to deal with the complicated network video data, the work focuses on the technologies of multilayer semantic mining and proxy cache for streaming media. Semantic mining method based on network parameter is presented. Quadratic regression popularity prediction model is introduced to analyze current popularity of streaming media. And then cache replacement strategy based on semantic mining is designed. Simulation results show that the cache replacement strategy is feasible and valid.
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基于语义挖掘的流媒体缓存替换策略
为了处理复杂的网络视频数据,重点研究了流媒体的多层语义挖掘和代理缓存技术。提出了基于网络参数的语义挖掘方法。引入二次回归流行度预测模型对当前流媒体流行度进行分析。然后设计了基于语义挖掘的缓存替换策略。仿真结果表明了该缓存替换策略的可行性和有效性。
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