基于谱聚类的Web多级缓存替换策略

服务器缓存性能的核心是缓存替换策略, 缓存替换策略直接影响缓存的命中率, Web缓存可以解决网络拥塞和用户访问延迟问题, 提高服务器的性能. 传统缓存替换算法的命中率往往不高, 为此文中提出了一种基于谱聚类的多级缓存替换策略. 该策略利用循环滑动窗口机制提取日志文件的多项时序特征和访问属性, 通过谱聚类对过滤后的数据集进行聚类分析从而得到访问预测结果. 多级缓存替换策略综合考虑了缓存对象的局部频率、全局频率以及资源大小能更好地对低价值资源进行剔除, 同时对高价值资源进行保留. 通过与传统替换算法LRU、LFU、RC、FIFO进行实验对比, 实验结果表明本文将谱聚类和多级缓存替换策略进行结合有效地提高了缓存请求命中率和字节命中率.

Replacement Strategy of Web Multi-cache Based on Spectral Clustering

The core of server cache performance is the cache replacement strategy which directly affects the cache hit ratio. Web cache can solve the problems of network congestion and user access delay and improve server performance. A multi-cache replacement strategy based on spectral clustering is proposed because of the low cache hit ratio of traditional cache replacement algorithms. The strategy uses the circular sliding window mechanism to extract multiple temporal features and access attributes of log files and conducts cluster analysis on the filtered data set through spectral clustering to obtain access prediction results. Multi-cache replacement strategy takes into account the local frequency, global frequency, and resource size of the cache object to eliminate the low-value resources and retain the high-value resources. In comparison with traditional replacement algorithms such as LRU, LFU, RC, and FIFO, the experimental results show that the combination of spectral clustering and multi-cache replacement strategy in this study can effectively improve the cache request hit ratio and byte hit ratio.