基于密度划分的分布式数据容错存储算法研究  

Research on Distributed Data Fault⁃Tolerant StorageAlgorithm Based on Density Partition

作　　者：翁锦阳[1] 朱铁兵[1] 柏志安[1] WENG Jinyang;ZHU Tiebing;BAI Zhian(Computer Centre,Ruijin Hospital,Shanghai Jiaotong University School of Medicine,Shanghai 200025,China)

机构地区：[1]上海交通大学医学院附属瑞金医院计算机中心,上海200025

出　　处：《吉林大学学报（信息科学版）》2024年第1期67-73,共7页Journal of Jilin University（Information Science Edition）

基　　金：上海市科技基金资助项目(202011000032)。

摘　　要：为保证数据安全性,缓解数据存储空间,提出基于密度划分的分布式数据容错存储算法。过滤分布式数据高密度数据区域,将具有高度相似的目标划分到不同区域,通过数据来源样本点描述数据的密度分布,设定数据弹性,利用概率以及数据粒度推算出对应的存储梯度和强度指数,并在信息存储中引入数据存储梯度和数据弹性,完成分布式数据容错存储。实验证明,所提算法有较高的容错性,带宽吞吐量平稳,平均路径长度较小,能提高网络数据的安全性。In order to ensure data security and alleviate data storage,a distributed data fault⁃tolerant storage algorithm based on density partitioning is proposed.High⁃density data areas of distributed data are filtered,highly similar targets are divided into different areas,the density distribution of data is described through data source sample points,the data elasticity is set,probability and data granularity is used to calculate the corresponding storage gradient and intensity index,and data storage gradient and data elasticity is introduced into information storage to complete distributed data fault⁃tolerant storage.Experiments show that the proposed algorithm has high fault tolerance,stable bandwidth throughput,small average path length,and can improve the security of network data.

关 键 词：密度划分 分布式数据 数据容错存储 数据粒度 强度指数 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]