A self-tuning client-side metadata prefetching scheme for wide area network file systems  

作　　者：Bing WEI Limin XIAO Yao SONG Guangjun QIN Jinbin ZHU Baicheng YAN Chaobo WANG Zhisheng HUO 

机构地区：[1]Laboratory of Software Development Environment,Beihang University,Beijing 100191,China [2]School of Computer Science and Engineering,Beihang University,Beijing 100191,China [3]Smart City College,Beijing Union University,Beijing 100101,China

出　　处：《Science China(Information Sciences)》2022年第3期74-90,共17页中国科学（信息科学）（英文版）

基　　金：supported by National key R&D Program of China (Grant No. 2018YFB0203901);National Natural Science Foundation of China (Grant No. 61772053);the Fund of the State Key Laboratory of Software Development Environment (Grant No. SKLSDE-2018ZX-10);Science Challenge Project (Grant No. TZ2016002)。

摘　　要：Client-side metadata prefetching is commonly used in wide area network(WAN) file systems because it can effectively hide network latency. However, most existing prefetching approaches do not meet the various prefetching requirements of multiple workloads. They are usually optimized for only one specific workload and have no or harmful effects on other workloads. In this paper, we present a new self-tuning client-side metadata prefetching scheme that uses two different prefetching strategies and dynamically adapts to workload changes. It uses a directory-directed prefetching strategy to prefetch the related file metadata in the same directory, and a correlation-directed prefetching strategy to prefetch the related file metadata accessed across directories. A novel self-tuning mechanism is proposed to efficiently convert the prefetching strategy between directory-directed and correlation-directed prefetching. Experimental results using real system traces show that the hit ratio of the client-side cache can be significantly improved by our self-tuning client-side prefetching. With regards to the multi-workload concurrency scenario, our approach improves the hit ratios for the no-prefetching, directory-directed prefetching, variant probability graph algorithm, variant apriori algorithm, and variant semantic distance algorithm by up to 15.22%, 6.32%, 10.08%, 11.65%, and10.73%, corresponding to 25.24%, 18.11%, 23.53%, 24.94%, and 24.19% reductions in the average access time, respectively.

关 键 词：wide area network file systems multiple workloads metadata prefetching correlation-directed prefetching directory-directed prefetching self-tuning prefetching 

分 类 号：TP393.2[自动化与计算机技术—计算机应用技术] TP311.13[自动化与计算机技术—计算机科学与技术]