基于预测的Web缓存替换策略

为提高Web缓存性能，在缓存替换算法的基础上加入预测机制，提出了基于预测的Web替换策略P-Re。预测算法采用PPM上下文模型，当缓存空间不够用来存放新的对象时，P-Re选择键值较小且未被预测到的对象进行替换。实验表明，基于预测的Web缓存替换算法P-Re相对于传统替换算法而言具有较高的命中率和字节命中率。     

一种基于对象属性的Web缓存替换策略

为了降低访问时延,提升用户体验,当前网络交互性能改进的主要手段包括缓存技术与预取技术。当前的缓存替换机制主要考虑对象的访问时间与访问频度,然而Web对象本身存在语义性。本文首先对实际Web数据访问情况进行分析,发现访问间隔的变化率对于命中率的影响具有更高的准确性,进而提出一种基于对象属性的缓存替换策略,该策略通过统计近期缓存对象的平均访问间隔,并结合该对象的标签属性作为对象在缓存中的价值。实验结果表明该策略比基于Aging的缓存策略和基于协作式中心化决策缓存策略提升7%-10%的命中率。     

基于高斯混合模型的Web代理服务器缓存替换策略

Web代理服务器缓存能够在一定程度上解决用户访问延迟和网络拥塞问题,Web代理缓存的缓存替换策略直接影响缓存的命中率,从而影响网络请求响应的效果;为此,使用一种通过固定大小的循环滑动窗口提取Web日志数据的多项特征,并使用高斯混合模型对Web日志数据进行聚类分析,预测在窗口时间内可能再次访问到Web对象,结合最近最少使用(LRU)算法,提出一种新的基于高斯混合模型的Web代理服务器缓存替换策略;实验结果表明,与传统的缓存替换策略LRU、LFU、FIFO、GDSF相比,该策略有效提高了Web代理缓存的请求命中率和字节命中率。     

代理缓存替换一致性算法的研究

代理缓存技术能很好的解决Internet发展中出现的访问延迟过长、服务器过载等一系列的问题.针对代理缓存的一致性策略和替换策略还没有很好地结合起来的技术现状,设计并实现了一种新的优化代理缓存的替换一致性算法-RCA算法.这种算法包括一致性策略和替换策略两部分,一致性策略采用自适应TTL机制,替换策略是结合了LFU和LRU,并引入老化机制的LFRU算法.通过Trace-Driven模拟实验,结果表明RCA算法在文档命中率和文档字节命中率比上均优于传统的几个替换算法.     

利用ZIPF定律建立有效的WEB对象缓存机制

通过对Web通信量的分析,人们发现用户对Web对象的访问模式服从Zipf定律或类Zipf定律。在Web缓存的设计中,为得到所期望的Web对象命中率的要求,设计人员可以根据Zipf定律近似计算出相应的缓存大小。因此,Zipf定律为Web缓存结构的设计提供了重要的依据。适当的缓存大小结合P-LFU替换策略可以得到很高的Web缓存命中率。     

Web缓存命中率与字节命中率关系

在研究Web缓存性能时,一般考虑2个评价指标：命中率HR和字节命中率BHR。目前大多侧重于2个指标之一,或仅通过测试2个指标的数值来评价缓存替换算法优劣,没有从2个指标关系的角度来评价缓存替换算法的性能。该文讨论了Web缓存系统中命中率与字节命中率之间的关系,提出了一种Web缓存性能评价指标——命中比（FBR）,讨论了该指标在Web缓存替换算法及Web预取性能评价中的应用,为度量缓存系统的性能提供了参考依据。     

基于比例命中率的Web缓存区分服务

基于反馈控制理论,通过系统辨识设计了缓存控制器。动态调整不同类别缓存对象的缓存空间,可保证高优先级Web对象的高命中率,而不同类别的Web对象命中率之比保持不变。在服务器端实现了基于比例命中率的缓存区分服务。经实验验证,在GDSF,LRU,LFU缓存替换算法下,无论是请求命中率还是字节命中率,均有良好的区分效果。     

基于机器学习的Web代理缓存替换策略性能改进

在Web代理缓存中,传统的缓存替换策略往往不够有效,会缓存一些不会再次被访问的Web对象。基于此,笔者使用机器学习技术对这部分Web对象进行过滤,使用Web代理日志文件进行训练,以预测Web对象的类别。实验结果表明,与最近最少使用（Least Recently Used,LRU）替换策略相比,使用机器学习技术的命中率最大提高了18.92%,字节命中率最大提高了45.61%。     

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.     

基于NB分类器重访概率预测的Web缓存替换策略

Web缓存是用来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，提出一种朴素贝叶斯（NB）分类器重访概率预测的Web缓存替换策略；根据用户之前访问日志，通过分区操作提取多项特征来表示每次访问的对象，并构建特征数据集；训练NB分类器，用来确定缓存中对象被再次访问的概率，为对象分配权重；结合LRU策略来合理删除一些对象。仿真结果表明，提出的策略在保证较高命中率的同时有效降低了执行时间。     

Web合作缓存置换算法的改进与实现

在LRU算法的基础上,提出一种改进的Web合作缓存置换算法。该算法针对不同大小的文档采取不同的存储策略,如增加小文档在缓存组中的存储数量,以提高其本地缓存的命中率,减少大文档在缓存组中存储的数量,以节约整个缓存组的空间。仿真实验结果表明该算法能够获得较好的性能。     

基于对象角色的高精度缓存替换算法*

现有的Web缓存器的实现主要是基于传统的内存缓存算法,由于Web业务请求的异质性,传统的替换算法不能在Web环境中有效工作。研究了Web缓存替换操作的依据,分析了以往替换算法的不足,考虑到Web文档的大小、访问代价、访问频率、访问兴趣度以及最近一次被访问的时间对缓存替换的影响,提出了Web缓存对象角色的概念,建立了一种新的基于对象角色的高精度Web缓存替换算法(ORB算法);并以NASA和DEC的代理服务器数据为例,将该算法与LRU、LFU、SIZE、Hybrid算法进行了仿真实验对比,结果证明,ORB算     

一种新的代理缓存替换策略

代理缓存的替换策略事实上可以看做排序问题，排序的标准可能有多种，寻找一个好的代理缓存的替换策略就是寻找一个能够反映真实Web访问特性的标准，基于文档大小的替换策略是一种简单实用的策略，但是并未全部利用WWW访问特性，根据在代理缓存日志中对各种访问特性的分析，使用文档大小，访问频率、文档访问剩余寿命作为计算文档价值的要素，提出了一种新的替换策略，这种策略同时具有较高的文档命中率和文档字节命中率，最后给出了基于日志的模拟。     

Proxy Cache Replacement Algorithms: A History-Based Approach

Accesing and circulation of Web objects has been facilitated by the design and implementation of effective caching schemes. Web caching has been integrated in prototype and commercial Web-based information systems in order to reduce the overall bandwidth and increase system's fault tolerance. This paper presents an overview of a series of Web cache replacement algorithms based on the idea of preserving a history record for cached Web objects. The number of references to Web objects over a certain time period is a critical parameter for the cache content replacement. The proposed algorithms are simulated and experimented under a real workload of Web cache traces provided by a major (Squid) proxy cache server installation. Cache and bytes hit rates are given with respect to different cache sizes and a varying number of request workload sets and it is shown that the proposed cache replacement algorithms improve both cache and byte hit rates.     

Performance evaluation of Web proxy cache replacement policies

The continued growth of the World-Wide Web and the emergence of new end-user technologies such as cable modems necessitate the use of proxy caches to reduce latency, network traffic and Web server loads. In this paper we analyze the importance of different Web proxy workload characteristics in making good cache replacement decisions. We evaluate workload characteristics such as object size, recency of reference, frequency of reference, and turnover in the active set of objects. Trace-driven simulation is used to evaluate the effectiveness of various replacement policies for Web proxy caches. The extended duration of the trace (117 million requests collected over 5 months) allows long term side effects of replacement policies to be identified and quantified.

Our results indicate that higher cache hit rates are achieved using size-based replacement policies. These policies store a large number of small objects in the cache, thus increasing the probability of an object being in the cache when requested. To achieve higher byte hit rates a few larger files must be retained in the cache. We found frequency-based policies to work best for this metric, as they keep the most popular files, regardless of size, in the cache. With either approach it is important that inactive objects be removed from the cache to prevent performance degradation due to pollution.     

A new cache document replacement policy considering the contribution to sales

Most traditional cache document replacement policies are focused on the efficiency aspect and these documents are replaced according to their last access times, request frequencies, and sizes. However, in addition to providing efficient document acquisition service, a successful commercial website also has to create incentives for customers, so as to gain sufficient revenues to support the continuing operation of the website. For this reason, a new cache document replacement policy considering the contribution-to-sales of every document is proposed in this study. In order to evaluate the contribution-to-sales of a document, two web mining techniques are applied. Then the traditional GDSF policy is modified to incorporate this new factor. To evaluate the effectiveness of the proposed methodology, an experimental EC website has been constructed, and a series of computer programs have been developed to simulate the accesses by various kinds of users to the website and to obtain some data for rudimentary analyses. The results showed that the proposed replacement policy could at most increase the hit rate and the byte hit rate by 16% and 9%, respectively, for customers compared with traditional replacement policies.     

Evolutionary Techniques for Web Caching

Web caching has been proposed as an effective solution to the problems of network traffic and congestion, Web objects access and Web load balancing. This paper presents a model for optimizing Web cache content by applying either a genetic algorithm or an evolutionary programming scheme for Web cache content replacement. Three policies are proposed for each of the genetic algorithm and the evolutionary programming techniques, in relation to objects staleness factors and retrieval rates. A simulation model is developed and long term trace-driven simulation is used to experiment on the proposed techniques. The results indicate that all evolutionary techniques are beneficial to the cache replacement, compared to the conventional replacement applied in most Web cache server. Under an appropriate objective function the genetic algorithm has been proven to be the best of all approaches with respect to cache hit and byte hit ratios.