基于弹性空间模型的实验室网络数据存储算法
Laboratory Network Data Storage Algorithm Based on Elastic Space Model
万晓云 1张泰 2程妍2
作者信息
- 1. 湖南信息学院计算机科学与工程学院,湖南 长沙 410151
- 2. 湖南农业大学信息与智能科学技术学院,湖南 长沙 410128
- 折叠
摘要
开放实验室网络系统海量数据会加重云端处理中心负担,降低了数据云存储性能.为解决上述问题,提出一种基于弹性空间模型的实验室网络数据存储算法.数据云存储量大导致数据链路存在冗余问题,为此对开放实验室网络数据实施清洗处理,构建弹性空间模型,通过该模型获取网络感知数据在近邻空间中的波动变化,达到降低网络能耗的目的;依据数据预处理结果,构建网络数据云存储模型,利用该模型对网络数据实施海量云调度转存,实现网络数据云存储.实验结果表明,通过对该方法开展网络数据可用性对比、数据节点均衡性对比,验证了上述方法的可行性强、实用性高.
Abstract
The massive amount of data in the open laboratory network system will increase the burden on the cloud processing center and reduce the performance of data cloud storage.To address the aforementioned issues,a laboratory network data storage algorithm based on an elastic space model was proposed.Due to the redundancy problem caused by large data cloud storage,the data in open laboratory network was cleaned,and then an elastic space model was con-structed.Based on this model,the fluctuation of network perception data in the nearest neighbor space was obtained,thus reducing network energy consumption.According to the data preprocessing result,a cloud storage model was con-structed to achieve the massive cloud scheduling for network data.The experimental results show that the feasibility and practicality of this method have been verified through comparing network data availability and data node balance.
关键词
开放实验室/数据云存储/数据清洗/系统能耗Key words
Open laboratory/Data cloud storage/Data cleaning/Energy consumption of system引用本文复制引用
出版年
2024
NETL
NSTL
万方数据