期刊文献+

基于窄带物联网的信息压缩存储方法 被引量:1

Information Compression Storage Method Based on Narrowband Internet of Things
下载PDF
导出
摘要 为解决大数据集冗余过大和有效存储时面临存储空间不足的问题,提出基于窄带物联网的信息压缩存储方法。首先使用移动采集感知层中的智能终端采集装置获取所需信息,然后利用窄带物联网将所得信息传输到网络层的LoRa网关汇聚节点,由汇聚节点负责整合接收到的信息,并将整合结果传输到应用层。应用层中的压缩存储模块运用了规范Hadamard矩阵,将接收到的信息压缩存储至数据库中,用户通过管理计算机可操作数据库内信息并查看返回结果。实验结果表明,上述的信息压缩时间和解压时间比方法使用前节约50%以上,且信息压缩比始终介于75%-90%之间;上述方法能在保留信息高度密集区域基本特征临界信息的同时,有效节约了信息存储空间。 In order to solve the problem of excessive redundancy of Big data sets and insufficient storage space in effective storage,this paper presented a method of compact storage for information based on NB-IoT.Firstly,the intelligent terminal acquisition device in mobile sensing layer was used to obtain the required information,and then NBIoT was used to transmit the information to the sink node of LoRa gateway in network layer.Secondly,the sink node was responsible for integrating the received information and transmitting the integration result to the application layer.The compression storage module in application layer made utilized a standard Hadamard matrix to compress and store the received information into the database.Finally,users can manipulate the information in the database and view the returned results through the management computer.Experimental results show that the compression time and decompression time of information are saved by more than 50%after using the proposed method.In the meanwhile,the information compression ratio is always between 75%-90%.We can see that this method effectively saves the information storage space while retaining the critical information of the basic features of the highly intensive area of information.
作者 桑振 胡建 SANG Zhen;HU Jian(Agricultural University of Hebei Province,Baoding Hebei 071000,China)
机构地区 河北农业大学
出处 《计算机仿真》 北大核心 2023年第9期426-430,共5页 Computer Simulation
关键词 窄带物联网 信息压缩存储 移动采集感知 网络层 应用层 Narrowband internet of things(NB-loT) Compressed storage of information Mobile acquisition and perception Network layer Application layer
  • 相关文献

参考文献11

二级参考文献91

共引文献87

同被引文献1

引证文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部