Cache prefetching strategy based on selective Markov model

CAI Wei-hong1; XIAO Shui2; WEI Gang1; XIONG Zhi2; HUANG Min-hua2

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Cache prefetching strategy based on selective Markov model

更新时间：2024-10-14

- Cache prefetching strategy based on selective Markov model
- Vol. 31, Issue 2, Pages: 58-66(2010)
- 作者机构：
  
  1. 华南理工大学电子与信息学院
  2. 汕头大学计算机系
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN919.8
- Published：2010
- 稿件说明：
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CAI Wei-hong1, XIAO Shui2, WEI Gang1, et al. Cache prefetching strategy based on selective Markov model[J]. 2010, 31(2): 58-66.
DOI：

CAI Wei-hong1, XIAO Shui2, WEI Gang1, et al. Cache prefetching strategy based on selective Markov model[J]. 2010, 31(2): 58-66. DOI：

摘要

通过分析研究现有流媒体缓存管理算法和用户的访问行为特征

提出了一种新的基于选择性马尔可夫模型的缓存预取策略。该策略通过序列合并方法对用户访问拖曳行为进行建模

采用状态剪枝优化方法FP

like得到选择性马尔可夫模型FPMM

并在此之上结合替换算法LRU-2构建出一种流媒体代理服务器缓存预取机制FPVlike

RU-2。仿真结果表明

在访问延时降低量方面

FPVlike

RU-2要比FP

RU-2、SP

RU-2、LRU-2分别高出10%、12%、17%

且在最佳的情况下该值能够达到60%以上。

Abstract

Through analyzing the existing streaming media cache management algorithm and user’s watching behavior characteristics

a new cache prefetching strategy based on selective Markov model was presented.The strategy

by mod-eling the user’s VCR action of choosing the merging sequence method

applied the FP

like method to get the selective Markov model FPMM

like and built a streaming media proxy cache prefetching mechanism FP

like-LRU-2 by com-bining the replacement algorithm LRU-2.The experimental results show that

like-LRU-2 is 10%、12%、17% higher than FP

RU-2

RU-2 and LRU-2 respectively in reducing latency experienced by users

and this value is able to reach over 60% in the ideal situation.

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Related Institution

State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications

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