摘要
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。
Establishing an accurate cache analysis model helps to predict the cache behavior better,which is vital for network performance analysis and planning.However,existing analysis models for cache consistency studies are based on the Least Recently Used(LRU)cache replacement strategy.However,different cache replacement strategies such as LRU,q-LRU,First In First Out(FIFO),etc,are required in real-world environments,depending on the application scenario and cache node capability.This study establishes an analysis model for generic cache strong consistency based on the basic assumptions of cache modeling to expand the scope of application of strong consistency strategies.Additionally,this study presents calculation methods for the cache hit ratio and server load under three cache strong consistency strategies(reactive invalidation,proactive invalidation with removing,and proactive invalidation with renewing).The model calculation results are used to plot the cache parameters to determine the parameters that optimize the cache performance and analyze to select the optimal cache replacement strategy for the given cache parameters.The experimental results show that the model has high computational accuracy under three cache strong consistency strategies.The maximum error between the computational and simulation results is 6.92%,and the minimum error is 0.06%.The proposed model is applicable to all cache replacement strategies that can be approximated based on the characteristic time.
作者
杨涛
郑烇
徐正欢
施钱宝
彭思伟
YANG Tao;ZHENG Quan;XU Zhenghuan;SHI Qianbao;PENG Siwei(Laboratory of Future Networks,Department of Automation,University of Science and Technology of China,Hefei 230026,China;Institute of Artificial Intelligence,Hefei Comprehensive National Science Center,Hefei 230088,China;Institute of Advanced Technology,University of Science and Technology of China,Hefei 230031,China)
出处
《计算机工程》
CAS
CSCD
北大核心
2022年第12期180-188,195,共10页
Computer Engineering
基金
国家重大科技基础设施未来网络试验设施项目(2016-000052-73-01-000515)
安徽省重点研发计划“可重构高通量网络检测仪研究”(202004a05020078)。
关键词
缓存
一致性
替换策略
特征时间
缓存命中率
服务器负载
cache
consistency
replacement strategy
characteristic time
cache hit ratio
server load