Research and improvement of cloud storage for massive small files

Xiao Liu, R. Xie, Guozhen Shi, Kaishi Guo
{"title":"Research and improvement of cloud storage for massive small files","authors":"Xiao Liu, R. Xie, Guozhen Shi, Kaishi Guo","doi":"10.1109/IICSPI48186.2019.9095888","DOIUrl":null,"url":null,"abstract":"Cloud storage for massive small files has become the trend of data storage in network cloud environment. How to ensure small files meet user needs and secure storage is a major challenge in cloud storage research. Aiming at the above challenges, this paper improves the existing FastDFS system, divides the storage space into four levels, and stores different levels according to the user's account level, thus solving the problem of user demand. In order to improve the efficiency of file reading and writing, this paper puts forward the placement strategy of massive small files and the selection of small file retrieval algorithm. Through MD5 algorithm, a secondary index is established to make files easier to store. Theoretical analysis shows the security and performance of the system, which solves the problem of access security of massive small files in cloud storage, and effectively improves the efficiency of reading and writing under the premise of ensuring security.","PeriodicalId":318693,"journal":{"name":"2019 2nd International Conference on Safety Produce Informatization (IICSPI)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 2nd International Conference on Safety Produce Informatization (IICSPI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IICSPI48186.2019.9095888","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Cloud storage for massive small files has become the trend of data storage in network cloud environment. How to ensure small files meet user needs and secure storage is a major challenge in cloud storage research. Aiming at the above challenges, this paper improves the existing FastDFS system, divides the storage space into four levels, and stores different levels according to the user's account level, thus solving the problem of user demand. In order to improve the efficiency of file reading and writing, this paper puts forward the placement strategy of massive small files and the selection of small file retrieval algorithm. Through MD5 algorithm, a secondary index is established to make files easier to store. Theoretical analysis shows the security and performance of the system, which solves the problem of access security of massive small files in cloud storage, and effectively improves the efficiency of reading and writing under the premise of ensuring security.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
海量小文件云存储的研究与改进
海量小文件的云存储已成为网络云环境下数据存储的趋势。如何保证小文件满足用户需求和安全存储是云存储研究的主要挑战。针对以上挑战,本文对现有FastDFS系统进行了改进,将存储空间划分为四层,并根据用户的账户级别存储不同的级别,从而解决了用户需求问题。为了提高文件读写效率,本文提出了海量小文件的放置策略和小文件检索算法的选择。通过MD5算法建立二级索引,使文件更易于存储。理论分析表明了系统的安全性和性能,解决了云存储中海量小文件的访问安全问题,在保证安全的前提下有效提高了读写效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
The Analysis and Design of System of Experimental Consumables Based on Django and QR code Analysis and Research on the Characteristics of Boiled Yolk based on Hyperspectral Remote Sensing Images Density Peaks Spatial Clustering by Grid Neighborhood Search Modeling of Superheated Steam Temperature Characteristics Based on Fireworks Algorithm Optimized Extreme Learning Machine Fusion Chaotic Prediction Model for Bearing Performance by Computer Technique
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1