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System Development & Application
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831-835

File system caching algorithm based on frequent sequence mining

Du Kexinga
Zhang Xiaofangb
Zhang Xiaob
Zhao Xiaonanb
a. College of Software, b. College of Computer, Northwestern Polytechnical University, Xi'an 710072, China

Abstract

Traditional cache algorithms have problems such as low hit rate and high exchange rate. And the existing caching algorithm is not applicable in the distributed big data storage system. This paper proposed an adaptive caching strategy based on frequent sequence mining. This method used a data mining algorithm to mine the frequent sequences in the historical access window, and merged the frequent sequences to construct a set of matching patterns for query. When a new access coming, matched the subsequence within the fixed access length with the matching pattern set, and then prefetched the data according to the matching result, and combined with the modified S4LRU(4-segmented least recently used) data structure for cache data exchange out. This paper conducted simulation experiments on the public big data processing trace set. The experimental results show that, under different cache sizes, compared with the existing typical cache algorithms, the proposed algorithm increases the average hit rate by 0.327 times and the average exchange rate reduces by 0.33 times, at the same time has the characteristics of low overhead and high time efficiency. This result shows that the proposed method is a more effective caching strategy than the traditional replacement algorithm.

Foundation Support

国家重点研发计划资助项目(2018YFB1004401)
北京市自然科学基金—海淀原始创新联合基金资助项目(L192027)
陕西省重点产业链项目(2021ZDLGY03-02,2021ZDLGY03-08)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.08.0337
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 3
Section: System Development & Application
Pages: 831-835
Serial Number: 1001-3695(2022)03-032-0831-05

Publish History

[2021-11-22] Accepted Paper
[2022-03-05] Printed Article

Cite This Article

杜科星, 张小芳, 张晓, 等. 基于频繁序列挖掘的文件系统缓存算法设计 [J]. 计算机应用研究, 2022, 39 (3): 831-835. (Du Kexing, Zhang Xiaofang, Zhang Xiao, et al. File system caching algorithm based on frequent sequence mining [J]. Application Research of Computers, 2022, 39 (3): 831-835. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.


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