一种基于用户的LNS文件预测模型  

User-based LAST N Successors file prediction model

作　　者：刘爱贵[1] 陈刚[1] 

机构地区：[1]中国科学院高能物理研究所计算中心

出　　处：《计算机工程与应用》2007年第29期14-16,39,共4页Computer Engineering and Applications

基　　金：国家自然科学基金( the National Natural Science Foundation of China under Grant No.90412017)

摘　　要：许多系统把数据访问请求当作是独立的事件。实际上,数据请求并非完全随机,而是由用户或程序的行为驱动的,不同的用户或程序存在不同的访问模式。LS(Last Successor)模型简单,但非常有效,然而它的预测结果严重依赖于用户或程序的访问顺序。提出了ULNS(User-based Last N Successors)文件预测模型,利用用户信息来提高预测精确度,并综合LS模型来改进算法的可适用度。实验结果表明,该预测模型具有较好的整体性能。Most systems treat each data request as an independent event.In fact,such requests are driven by users or programs behavior,and are therefore far from random.There are different access patterns with different users or programs.LS（Last Successor） model is simple,but very available.However,its predictive results strongly depend on access order of users or programs.This paper presents ULNS（User-based Last N Successors） file prediction model,which utilizes user information to improve its accuracy.And also,it synthesizes LS model to extend its applicability.Experimental results show that the proposed prediction model has better overall performances.

关 键 词：文件访问模式 预测模型 预测精确度 可适用度 

分 类 号：TP33[自动化与计算机技术—计算机系统结构]