一种改进的自适应页面置换算法

研究缓冲区页面置换策略和算法(特别是自适应页面置换策略和算法),提出一种基于双管理链的自适应页面置换算法HA。HA算法是对DMC(2c)算法的改进,它引入动态置换点,同时,根据缺页失败数确定算法的工作链,并根据页面访问序列的局部特征选择效率较高的页面置换策略。实验结果表明,HA算法能有效地减少缺页失败数,降低缺页率,特别是在处理第三种模式的页面访问序列时,该算法的缺页率较改进前的算法可降低近30%。     

基于局部性定量分析模型的自适应替换算法LA-LRFU

已有的LRFU(Least Recency Frequency Used)自适应算法在实际应用中根据经验调整λ值,缺乏对访问局部性强弱的量化分析,因而其可适用的访问模式有限.该文首先建立基于K阶马尔可夫链(K→∞)的局部性定量分析模型,在访问过程中根据统计信息实时量化局部性特征.然后以此分析模型为基础设计自适应替换算法LA-LRFU(Locality-Aware LRFU),随着访问特征的变化动态调整参数λ.最后应用Trace仿真对算法进行测试.实验结果显示,针对多种访问模式,LA-LRFU均可显著提高Cache命中率;在由多种访问模式构成的具体访问过程中,LA-LRFU能比现有的各类LRFU自适应算法更合理地调整参数λ.     

对页面访问序列影响LRU页面置换算法的研究

页面置换算法是操作系统中虚拟存储管理的一个重要部分。改进页面置换算法,可以降低页面失败率,从而有效地提高系统性能。现有的应用于虚拟存储管理的页面置换算法主要是Least Reference Used(LRU)页面置换算法。文中利用页面访问间隔数,分析不同的页面访问序列对LRU算法的影响,把页面访问序列分为LRU-友好页面访问序列、LRU-不友好页面访问序列、不友好页面访问序列三类,为改进LRU页面置换算法提供了依据。     

文件Cache自适应策略研究

Linux系统在被不同大小的数据块访问时,系统读写性能有差异。在少数特定访问数据块大小的应用中,Linux系统读写性能较差。文件Cache算法的性能是导致该问题的原因之一。在分析访问数据块大小对文件Cache算法性能的影响的基础上,提出了一种文件Cache自适应策略。该策略考虑了预取算法对于页面置换算法的影响,增强了页面置换算法对访问数据块大小变化的适应性,达到了提高Linux系统读写性能的目标。Linux系统读写性能测试实验表明,该策略可以使Linux系统在被不同大小的数据块访问时保持稳定且更优的读写性能。     

对页面访问序列影响LRU页面置换算法的研究

页面置换算法是操作系统中虚拟存储管理的一个重要部分。改进页面置换算法，可以降低页面失败率，从而有效地提高系统性能。现有的应用于虚拟存储管理的页面置换算法主要是Least Reference Used（LRU）页面换算法。文中利用页面访问间隔数，分析不同的页面访问序列对LRU算法的影响，把页面访问序列分为LRU-友好页面访问序列、LRU-不友好页面访问序列、不友好页面访问序列三类，为改进LRU页面置换算法提供了依据。     

基于ARC的闪存数据库缓冲区算法

闪存是一种纯电子设备,具备体积小、数据读取速度快、能耗低、抗震性强等优点,被用来部分替代机械硬盘从而提升存储系统的性能.但是,现有的缓冲区置换算法都是针对机械硬盘的物理特性进行设计和优化,因此有必要针对闪存的物理特性重新设计缓冲区置换算法.提出一种新的面向闪存数据库的缓冲区替换算法CF-ARC.算法设计了一种新的页替换机制,即在替换干净页或者脏页的时候考虑其访问频度的大小,优先将访问频度少的干净页替换出缓冲区,使得热页继续留在缓冲区提高命中率,从而获得更好的性能,通过对实验结果的对比分析发现CF-ARC在多数情况下具有比其它置换算法更高的性能.     

闪存数据库缓冲区置换算法综述

随着闪存技术的发展和闪存容量的不断增大,闪存存储被广泛应用,给闪存数据库管理带来机遇和挑战。因为闪存和磁盘读写方式不同,读写性能也有差别,所以对于闪存缓冲区的管理成为一个亟待解决的问题。为了提高闪存的访问性能,缓冲区置换算法在保证命中率的同时要尽量减少写和擦除操作的次数。对主流的闪存数据库缓冲区置换算法进行分析,比较了几种算法的优点和不足,并给出了未来研究的方向。     

一种针对闪存的高效缓冲区置换算法

随着闪存容量的不断增长和闪存应用的日益广泛,针对闪存的缓冲区管理已成为一个迫切需要解决的问题.针对闪存的写代价显著高于读代价的特性,提出一种针对闪存的页面置换算法LEAC.LEAC根据页面的读写负载和闪存的读写代价差异对换出页面引起的预期闪存访问开销进行评估,优先换出预期访问开销最低的页.实验表明,LEAC可以显著降低闪存访问开销.     

优化的R-树缓冲管理算法

在分析Ｒ－枝操作特性和ＬＲＵ算法的基础上,提出了一种新的基于ＬＲＵ的Ｒ－树缓冲管理算法ＰＩＮ－ＬＲＵ。该算法对Ｒ－树访问路径上的节点进行标记,动态地在缓冲区中将访问路径上的节点加“钉”和释放“钉”,从而尽可能减少不必要的内－外存数据交换,提高Ｒ－树缓冲管理的效率,实验表明,ＰＩＮ－ＬＲＵ算法在磁盘Ｉ／Ｏ和页面访问命中率等方面均优于ＬＲＵ算法。     

LRU页面置换算法的改进与实现

为简化嵌入式虚拟内存的实现,改善嵌入式虚拟内存的性能,在对常见页面置换算法进行对比分析的基础上,提出一种改进的最久未使用页面置换算法。该算法基于内存管理单元、跨页访问计数器、访问次序寄存器、溢出中断处理等软硬件相结合的技术。实验结果表明,该算法能提高嵌入式系统的页面置换效率,提升系统的整体性能,可广泛应用于各种物联网系统和嵌入式系统。     

Window‐LRFU: a cache replacement policy subsumes the LRU and window‐LFU policies

Replacement algorithms have been widely used as key technologies for cache management in areas such as file systems or database management. A replacement algorithm determines which page to be evicted when the cache is full and a new page is referenced. Because replacement policies considering only recency or frequency such as LRU (Least Recently Used) and LFU (Least Frequently Used) do not perform well, replacement polices that take both recency and frequency into account have been intensively studied. As a classical replacement policy, LRFU (Least Recently/Frequently Used) policy subsumes the LRU and LFU policy. However, because LFU is not able to adapt to the change of page accessing pattern and it is hard to select a suitable λ for each certain trace, LRFU cannot always guarantee a good performance. In this paper, we propose a Window‐LRFU policy, to subsume the LRU and Window‐LFU policies. Experimental results show that the Window‐LRFU policy outperforms LRFU and has at least competitive performance than other classical algorithms. Copyright © 2015 John Wiley & Sons, Ltd.     

Ubase数据库系统缓冲管理器的实现

缓冲区技术是减少系统对外存访问的重要方法之一。文章分析了Ubase数据库系统缓冲管理器的基本功能,对常用页面替换算法的性能进行了比较,最终选择Love/Hate算法代替LRU算法实现了Ubase数据库系统的缓冲管理,降低了系统的开销,提高了Ubase数据库系统的性能。     

On using cache conscious clustering for improving OODBMS performance

The two main techniques of improving I/O performance of Object Oriented Database Management Systems (OODBMS) are clustering and buffer replacement. Clustering is the placement of objects accessed near to each other in time into the same page. Buffer replacement involves the selection of a page to be evicted, when the buffer is full. The page evicted ideally should be the page needed least in the future. These two techniques both influence the likelihood of a requested object being memory resident. We believe an effective way of reducing disk I/O is to take advantage of the synergy that exists between clustering and buffer replacement. Hence, we design a framework, whereby clustering algorithms incorporating buffer replacement cache behaviour can be conveniently employed for enhancing the I/O performance of OODBMS. We call this new type of clustering algorithm, Cache Conscious Clustering (C3). In this paper, we present the C3 framework, and a C3 algorithm that we have developed, namely C3-GP. We have tested C3-GP against three well known clustering algorithms. The results show that C3-GP out performs them by up to 40% when using popular buffer replacement algorithms such as LRU and CLOCK. C3-GP offers the same performance as the best existing clustering algorithm when the buffer size compared to the database size is very small.     

PostgreSQL闪存缓冲区置换算法扩展与性能验证

针对闪存缓冲区置换算法的性能验证基本采用仿真模拟的现状,提出了一种基于PostgreSQL的有说服力的性能验证方法,重点讨论了在PostgreSQL上扩展闪存缓冲区置换算法的方法和实现技术,并以CFLRU(clean first least recently used)和CCFLRU(cold clean first least recently used)算法为例,给出了具体的扩展过程。然后以一块固态硬盘作为数据存储设备进行性能测试,测试结果证明了基于PostgreSQL的扩展方法在缓冲区置换算法性能验证上的有效性。     

基于探测的自适应页面置换算法研究

页面置换算法是虚拟存储管理的重要组成部分,页面置换算法的优劣将直接影响系统的整体性能。本文在分析传统页面置换算法存在不足的基础上,介绍一种能够弥补传统页面置换算法存在不足的基于探测的自适应页面置换算法,同时分忻了该算法的性能,并且指出了进一步的研究方向。     

Optimal secondary storage access sequence for performing relationaljoin

Two graph models are developed to determine the minimum required buffer size for achieving the theoretical lower bound on the number of disk accesses for performing relational joins. Here, the lower bound implies only one disk access per joining block or page. The first graph model is based on the block connectivity of the joining relations. Using this model, the problem of determining an ordered list of joining blocks that requires the smallest buffer is considered. It is shown that this problem as well as the problem of computing the least upper bound on the buffer size is NP-hard. The second graph model represents the page connectivity of the joining relations. It is shown that the problem of computing the least upper bound on the buffer size for the page connectivity model is also NP-hard. Heuristic procedures are presented for the page connectivity model and it is shown that the sequence obtained using the heuristics requires a near-optimal buffer size The authors also show the performance improvement of the proposed heuristics over the hybrid-has join algorithm for a wide range of join factors     

Time-shift replacement algorithm for main memory performance optimization

Page replacement algorithms of main memory in modern operating systems are crucial in system performance. When memory is full, a page replacement algorithm exploits temporal locality and frequency of page references to evict the page that is least likely to be accessed in the near future. Subsequently, loading the majority of data directly from memory improves performance by reducing I/O waits of accessing slow storage. Research of replacement algorithms that maximizes hit ratio while incurring as less overhead as possible has been constantly studied. In this paper, we propose a time-shift least recently used (TSLRU) algorithm that converts frequency information of page references into temporal locality. Frequent accesses of a page are thus recognized and accumulated in terms of time. Moreover, pages being loaded into memory for the first time are not necessarily the most recently used pages. As a result, one-pass pages are evicted sooner in our algorithm than in traditional LRU algorithm. Our performance evaluations show that the TSLRU outperforms conventional page replacement algorithms on both artificial and real application traces. For example, hit ratio of TSLRU advances ARC by \(4.17\%\) and LRU by \(5.91\%\) on normal distributed workloads. Moreover, TSLRU outperforms ARC by over \(2\%\) on half of the application traces tested.     

面向网络流量的缓存替换算法比较与分析

缓存替换算法对优化网络处理应用的性能起到关键作用，但目前面向网络流量的缓存替换算法研究主要集中在算法设计和领域应用方面，较少有文献对现有的缓存替换算法在网络环境下的性能进行分析比较。对此，本文针对主要的6种缓存替换算法进行分析和比较。通过分析网络流量的新近度与频度特征，为基于最近最少使用(Least Recently Used, LRU)和最近最不常使用(Least Frequently Used, LFU)的缓存替换算法给出实际依据。对仿真环境和实际系统的实验结果表明，类LRU算法较LFU算法更适用于网络流量，而缓存空间较大时，随机替换算法较LRU算法更适用于多核环境。