基于语义贡献值的XML查询缓存替换策略

传统缓存替换策略对语义缓存替换缺乏针对性,不能有效重用缓存中的数据,影响缓存命中率。为此,针对可扩展标记语言查询(XML)代数查询的特点,提出一种基于语义贡献值的XML查询缓存替换策略,根据用户历史查询的缓存项进行聚类分析,预测其对未来查询的语义贡献值,当缓存空间不足时替换语义贡献值最小的项,从而提高用户查询效率。实验结果表明,相比最不经常使用策略和最近最少使用策略,该策略能有效缩短查询时间,提高缓存命中率。     

移动查询缓存处理的研究

客户缓存为提高客户／服务器数据库系统整体性能以及客户方数据可用性提供了有效途径。移动环境下网络资源的贫乏使客户缓存的作用更为重要，语义缓存是基于客户查询语义相关建立的一类缓存，提出一个基于语义缓存的客户缓存机制，给出缓存的内容组织，提出缓存项合并策略；然后讨论了基于语义缓存的查询处理策略；最后，模拟结果表明该客户缓存机制能够提高分布式、特别是移动环境下客户服务器数据库系统的性能。     

位置相关查询中基于最小访问代价的缓存替换方法

在位置相关查询（LDQ）中由于用户的移动性和数据的位置相关性,给缓存替换策略带来了新的挑战。在详细分析位置相关数据(LDD)的空间位置特性和几种典型的位置相关缓存替换策略的基础上,提出一种基于最小访问代价的缓存替换策略（PLAC）,一些重要的缓存替换因素如访问概率、更新频率、数据距离和有效范围等都包含在代价函数里,PLAC根据代价函数值的大小来决定被替换的数据,由此来保证有限缓存的最大使用率。通过实验对比,PLAC比其他位置相关缓存替换策略更为有效地提高了缓存命中率,缩短了查询平均响应时间。     

断接下查询的缓存处理

移动环境下，由于无线网络可靠性低、费用高，移动主机本身受电源、资源等方面的限制，移动主机经常会主动或被动地处于断接，即没有网络连接的状态．为了提高断接时移动客户对数据的访问能力，有效利用移动缓存，该文提出断接下基于语义缓存的查询处理QPID算法．该算法的主要思路是先找出缓存中与当前查询相关的缓存项，再通过对相关项数据的进一步处理获得缓存中满足查询的结果．试验表明，基于QPID算法的查询处理可以更好地满足断接下客户的查询请求．     

基于语义缓存的移动查询导出

在移动环境下，客户缓存为提高客户－服务器数据库系统的整体性能，特别是保证客户端数据可用性提供了有效途径，该文针对如何从基于语义描述的缓存中导出当前查询（部分）结果的问题，研究了查询从缓存导出的充分条件，并在定义查询与缓存之间的精确匹配，包含匹配和相互匹配几种情况的基础上，给出缓存与查询，包含与相交匹配的判断条件和相应的算法，基于该文的研究，查询可以充分利用本地语义缓存的内容，从而降低网络开销，加快响应时间，并支持移动客户断接时的数据访问。     

基于XQuery语义缓存的异构数据集成系统的查询处理

提出了一种在Mediator-Wrapper结构中嵌入基于XQuery语义缓存的异构数据集成系统的查询处理方案,主要包括查询包含关系判定、查询分解和重写.同时提出利用树型同态算法解决XQuery查询语义包含关系的判断问题和Web环境下的缓存替换策略,旨在提高信息集成系统的查询性能.     

位置感知查询中的协作缓存管理

位置感知查询（LAQ）是移动系统中常用的一种查询方式。提出了一种位置感知查询中的协作缓存管理技术（CoMA-LA）,该方法包括三方面的内容：（1）缓存中语义相近数据项的合并;（2）相邻缓存间的协作替换策略;（3）缓存间的数据一致性保证。通过仿真实验将CoMA-LA和传统的LRU算法以及一些已有的缓存替换方法进行了比较,实验结果表明采用CoMA-LA技术能够有效提高缓存利用率,从而降低平均访问时间,提高查询命中率。     

面向轨迹数据查询优化的缓存机制研究

移动对象数据库（Moving object database,MOD）管理随着时间不断改变位置的空间对象,其已经在广泛的应用中被研究。尽管索引和查询算法等许多与MOD相关的技术已经被提出,但缓存管理仍然被忽略,这对于数据库性能至关重要。传统的缓存方法忽视了数据本身的时空特性,无法实现良好的性能。本文提出从缓存层面充分挖掘轨迹数据的查询性能,首先针对轨迹数据特有的存储结构和读写过程,设计了适合MOD的缓存访问机制;然后对于MOD系统中缺少与应用场景和访问模式相关的缓存策略问题,定制了缓存替换方法;最后开发了缓存管理工具MOCache,以可视化的形式动态跟踪查询语句结束后缓存状态的变化。通过实验表明本文提出的缓存替换策略与传统的策略相比,命中率提高到76.56%,缩短了查询时间,并且使用缓存工具监控历史状态信息,能够更加全面地反馈和分析性能问题。     

通用缓存替换策略下的缓存强一致性研究

建立准确的缓存分析模型有助于更好地预测缓存行为,对于网络性能分析与规划具有重要作用。现有面向缓存强一致性研究的分析模型普遍基于最近最少使用（LRU）缓存替换策略,然而在实际环境中需要根据不同的应用场景和缓存节点能力采取LRU、q-LRU、先进先出等不同的缓存替换策略。为扩展缓存强一致性分析模型的适用范围,基于缓存建模的基本假设构建缓存强一致性通用分析模型,并给出被动查询、主动移除、主动更新3种缓存强一致性策略下缓存命中率和服务器负载的计算方法。利用模型计算结果绘制缓存参数变化曲线图找出使缓存性能达到最优的值,通过分析模型计算结果选出给定缓存参数时对应的最优缓存替换策略。实验结果表明,该模型在3种缓存强一致性策略下均具有较高的计算精确度,其中计算结果与仿真结果的最大误差和最小误差分别为6.92%和0.06%,适用于通过特征时间近似的缓存替换策略。     

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.     

A Framework for Cache Management for Mobile Databases: Design and Evaluation

In a mobile computing environment, database servers disseminate information to multiple mobile clients via wireless channels. Due to the low bandwidth and low reliability of wireless channels, it is important for a mobile client to cache its frequently accessed database items into its local storage. This improves performance of database queries and improves availability of database items for query processing during disconnection. In this paper, we investigate issues on caching granularity, coherence strategy, and replacement policy of caching mechanisms for a mobile environment utilizing point-to-point communication paradigm.We first illustrate that page-based caching is not suitable in the mobile context due to the lack of locality among database items. We propose three different levels of caching granularity: attribute caching, object caching, and hybrid caching, a hybrid approach of attribute and object caching. Next, we show that existing coherence strategies are inappropriate due to frequent disconnection in a mobile environment, and propose a cache coherence strategy, based on the update patterns of database items. Via a detail simulation model, we examine the performance of various levels of caching granularity with our cache coherence strategy. We observe, in general, that hybrid caching could achieve a better performance. Finally, we propose several cache replacement policies that can adapt to the access patterns of database items. For each given caching granularity, we discover that our replacement policies outperform conventional ones in most situations.     

Semantic caching of Web queries

Abstract. In meta-searchers accessing distributed Web-based information repositories, performance is a major issue. Efficient query processing requires an appropriate caching mechanism. Unfortunately, standard page-based as well as tuple-based caching mechanisms designed for conventional databases are not efficient on the Web, where keyword-based querying is often the only way to retrieve data. In this work, we study the problem of semantic caching of Web queries and develop a caching mechanism for conjunctive Web queries based on signature files. Our algorithms cope with both relations of semantic containment and intersection between a query and the corresponding cache items. We also develop the cache replacement strategy to treat situations when cached items differ in size and contribution when providing partial query answers. We report results of experiments and show how the caching mechanism is realized in the Knowledge Broker system. Received June 15, 1999 / Accepted December 24, 1999     

Performance evaluation of an optimal cache replacement policy for wireless data dissemination

Data caching at mobile clients is an important technique for improving the performance of wireless data dissemination systems. However, variable data sizes, data updates, limited client resources, and frequent client disconnections make cache management a challenge. We propose a gain-based cache replacement policy, Min-SAUD, for wireless data dissemination when cache consistency must be enforced before a cached item is used. Min-SAUD considers several factors that affect cache performance, namely, access probability, update frequency, data size, retrieval delay, and cache validation cost. The paper employs stretch as the major performance metric since it accounts for the data service time and, thus, is fair when items have different sizes. We prove that Min-SAUD achieves optimal stretch under some standard assumptions. Moreover, a series of simulation experiments have been conducted to thoroughly evaluate the performance of Min-SAUD under various system configurations. The simulation results show that, in most cases, the Min-SAUD replacement policy substantially outperforms two existing policies, namely, LRU and SAIU.     

一种超节点P2P网络中基于语义的协同缓存管理机制

超节点P2P（Super-peerP2P）结合了P2P结构和C／S结构的优点,是当前应用最广的一类P2P系统。在超节点P2P网络中,文件访问是最基本的操作,往往使用缓存技术来提高其操作效率。目前大多数超节点P2P网络使用传统的“尽力而为”的缓存机制,该机制没有区分超节点网络中不同节点对资源的需求及关注程度不同,导致偶尔访问的对象替换经常访问的对象。针对“尽力而为”缓存机制的不足,本文提出一种基于语义信息的协同缓存管理机制SCOCM（Semantic-based Cooperative Cache Management mechanism for super-peer net works）,应用已经请求对象的语义信息主动地选择对象放置缓存,以兴趣度的远近驱逐缓存内的对象,减少缓存对象的替换,使得每个缓存中缓存的对象之间尽可能地保持语义联系。实验结果表明,基于语义信息的协同缓存管理机制与LRU相比可大大降低缓存的替换率,提高缓存的存取效率,命中率也较高。     

Movement prediction based cooperative caching for location dependent information service in mobile ad hoc networks

Location Dependent Information Services (LDISs), through which mobile clients can access location sensitive data such as weather information, traffic reports, and local news, are gaining increasing popularity in recent years. Due to limited client power and intermittent connectivity, caching is an important approach to improve the performance of LDISs. In this paper, we propose a cache replacement policy called Location Dependent Cooperative Caching (LDCC). Unlike existing location dependent cache replacement policies, the LDCC strategy applies a prediction model to approximate client movement behavior and a probabilistic transition model to analyze the communication cost. These models are used in the design of a cache replacement policy to improve system overall performance. Simulation results demonstrate that the proposed strategy significantly outperforms existing caching policies in providing LDIS in mobile ad hoc networks.     

Policies for Caching OLAP Queries in Internet Proxies

The Internet now offers more than just simple information to the users. Decision makers can now issue analytical, as opposed to transactional, queries that involve massive data (such as, aggregations of millions of rows in a relational database) in order to identify useful trends and patterns. Such queries are often referred to as On-Line-Analytical Processing (OLAP). Typically, pages carrying query results do not exhibit temporal locality and, therefore, are not considered for caching at Internet proxies. In OLAP processing, this is a major problem as the cost of these queries is significantly larger than that of the transactional queries. This paper proposes a technique to reduce the response time for OLAP queries originating from geographically distributed private LANs and issued through the Web toward a central data warehouse (DW) of an enterprise. An active caching scheme is introduced that enables the LAN proxies to cache some parts of the data, together with the semantics of the DW, in order to process queries and construct the resulting pages. OLAP queries arriving at the proxy are either satisfied locally or from the DW, depending on the relative access costs. We formulate a cost model for characterizing the respective latencies, taking into consideration the combined effects of both common Web access and query processing. We propose a cache admittance and replacement algorithm that operates on a hybrid Web-OLAP input, outperforming both pure-Web and pure-OLAP caching schemes.     

基于时空局部性的层次化查询结果缓存机制

查询结果缓存可以对查询结果的文档标识符集合或者实际的返回页面进行缓存,以提高用户查询的响应速度,相应的缓存形式可以分别称之为标识符缓存或页面缓存。对于固定大小的内存,标识符缓存可以获得更高的命中率,而页面缓存可以达到更高的响应速度。该文根据用户查询访问的时间局部性和空间局部性,提出了一种新颖的基于时空局部性的层次化结果缓存机制。首先,该机制将固定大小的结果缓存划分为两层:页面缓存和标识符缓存。对于用户提交的查询,该机制会首先使用第一层的页面缓存进行应答,如果未能命中,则继续尝试使用第二层的标识符缓存。实验显示这种层次化的缓存机制较传统的仅依赖于单一缓存形式的机制,在平均查询响应时间上,取得了可观的性能提升:例如,相对单纯的页面缓存,平均达到9%,最好情况下达到11%。其次,该机制在标识符缓存的基础上,设计了一种启发式的预取策略,对用户查询检索的空间局部性进行挖掘。实验显示,这种预取策略的融合,能进一步促进检索系统性能的有效提升,从而最终建立起一套时空完备的、有效的结果缓存机制。