摘要
Web缓存用于解决网络访问延迟和网络拥塞问题,缓存替换策略直接影响缓存的命中率。为此,文中提出一种基于访问预测机制的Web缓存替换策略。首先,根据用户之前的访问日志,通过预处理操作提取多项特征以构建特征数据集。然后,通过训练支持向量机(SVM)分类器来预测缓存对象是否可能被再次访问,将分类为不会再次被访问的缓存对象删除以腾出空间。仿真结果表明,与传统的LRU,LFU和GDSF方案相比,提出的策略具有较高的请求命中率和字节命中率。
Web cache is used to solve the problems of network access delay and network congestion,and cache replacement strategy directly affects the hit rate of cache.For this reason,this paper proposed a database-level Web cache replacement strategy based on SVM access prediction mechanism.Firstly,according to previous access logs of users,a feature data set is constructed on the basis of extracting multiple features through a pre-processing operation.Then,a Support Vector Machine(SVM)classifier is trained to predict whether a cached object is likely to be accessed again in the future,and the cached objects that are classified as not being accessed are deleted to free memory.Simulation results show that,compared with the traditional LRU,LFU and GDSF schemes,this strategy has higher request hit rate and byte hit rate.
作者
杨瑞君
祝可
程燕
YANG Rui-jun;ZHU Ke;CHENG Yan(School of Computer Science and Information Engineering,Shanghai Institute of Technology,Shanghai 201418,China;School of Criminal Justice,East China University of Political Science and Law,Shanghai 201620,China)
出处
《计算机科学》
CSCD
北大核心
2019年第6期201-205,共5页
Computer Science
基金
国家自然科学基金(631233211)资助
关键词
WEB缓存
替换策略
访问预测机制
支持向量机
Web cache
Replacement strategy
Access prediction mechanism
Support vector machine
