摘要： 从数据份额属性间相关性的角度定量分析分布式存储网络中数据之间的关联。在此基础上提出一种分布式存储网络中数据更新的加权平均聚类算法，将相关的数据份额分布在不同网络节点上，使各节点上相关的数据保持相对分散。模拟实验结果表明，考虑数据相关性可以有效降低系统的失效概率。
关键词:
分布式存储网络,
数据相关性,
数据容错,
数据分离
Abstract: This paper analyzes the relevancy quantitatively in Distributed Storage Network(DSN) in the view of attributes relativity of data share. Based on the analysis, it presents a new mean-weight clustering algorithm in distributed storage networks based on the idea of dispersing correlative data share on different storage nodes. According to the simulative test, the algorithm can greatly lower compromising probability after taking the data relativity into consideration.
Key words:
Distributed Storage Network(DSN),
data relativity,
data fault-tolerance,
data dispersal
中图分类号:
朱率率;杨晓元;张 薇. 基于数据相关性的调度算法[J]. 计算机工程, 2010, 36(10): 80-82.
ZHU Shuai-shuai; YANG Xiao-yuan; ZHANG Wei. Schedule Algorithm Based on Data Relativity[J]. Computer Engineering, 2010, 36(10): 80-82.