面向云应用的存储缓存子系统  

Storage Caching Sub-system for Cloud Application

作　　者：蔡涛[1] 牛德姣[1] 张永春[1] 倪晓蓉[1] 周东明[1] 

机构地区：[1]江苏大学计算机科学与通信工程学院,镇江212013

出　　处：《计算机科学》2014年第4期195-199,210,共6页Computer Science

基　　金：高等学校博士学科点专项科研基金(20093227110005);广东省自然科学基金(S2011010006118);江苏省高校自然科学基金(09KJB520001);浙江省自然科学基金(LY13F020012)资助

摘　　要：性能是云应用的重要指标,云应用与现有应用在数据存储与管理方式和访问模式等方面存在较大差异,这使得传统的缓存管理算法难以适应云应用的要求.针对云应用的特性,设计了基于影响因子的缓存策略,亦即将元数据和数据缓存分开管理,使用影响因子综合管理影响缓存被再次访问的几率的多种因素,区别创建、打开、读取和修改等操作对缓存再次访问的几率的影响;设计了缓存关联管理策略,即利用元数据和数据之间的关联提高缓存管理的性能;设计了缓存主动调度策略,即通过主动淘汰较低影响因子的缓存项和动态调整元数据与数据缓存的大小来提高缓存子系统的适应能力和性能.最后实现了原型系统,并使用Filebench和Postmark进行了测试和分析,验证了面向云应用缓存子系统原型能提高1％～120％的I/O性能以及2％～87％的操作处理速度.Performance is very important for the cloud application.There are some differences between cloud and current application in management strategy and access pattern,which leads to the traditional cache management strategy can ＇t adapt to the requirement of the cloud application.According to the features of cloud application,the cache strategy based on impact factors was designed to implement the storage cache sub-system for cloud application.Metadata and dam cache were used to manage separately,making a distinction about the impact of the creation,opening,reading,writing and modifying on the probability of the cache accessed again.Then the two cache correlation strategics were designed to improve the performance of cache management according to the relation between metadata and data.The actively scheduling strategy was used to improve the adaptability based on eliminating the low impact factor cache entries actively and adjusting the space of metadata cache and data cache dynamically.At last,the prototype was released and was evaluated by Filenench and Postmark.The result shows the storage cache sub-system can improve 1％～120％ I/O performance and 2％～87％ operation processing speed.

关 键 词：缓存 云应用 文件系统 

分 类 号：TP316.4[自动化与计算机技术—计算机软件与理论]