基于物联网的分布式通信数据高效压缩仿真  

Efficient Compression Simulation of Distributed Communication Data Based on Internet of Things

作　　者：万川梅 朱参世[2] 唐宏[3] WAN Chuan-mei;ZHU Can-shi;TANG Hong(College of Computer,Chongqing Institute of Engineering,Chongqing 400056,China;Air Force Engineering University,Xi'an Shanxi 710038,China;College of Computer,Chongqing University of Posts and Telecommunications,Chongqing 400056,China)

机构地区：[1]重庆工程学院计算机学院,重庆400056 [2]中国人民解放军空军工程大学,陕西西安710038 [3]重庆邮电大学计算机学院,重庆400056

出　　处：《计算机仿真》2020年第6期410-415,共6页Computer Simulation

基　　金：重庆教委科学技术项目(KJQN201901910);重庆市教委高校创新研究群体项目(CXQTP19036);教育部产学合作协同育人项目(201802007002,201802180007);重庆市教委科研项目(KJQN201801902)。

摘　　要：针对物联网中节点能量是有限的,无法长时间支持通信网络的大量数据传输,导致传统数据压缩方法存在整合数据失误率高、数据压缩率低以及传感节点能量消耗快等问题,提出一种基于物联网的分布式通信数据高效压缩方法。通过物联网分布式结构分析边界效应,采用小波函数对不同节点传送的数据进行数据变换,根据Mallat算法,计算因数据变换而得到的低频系数和高频系数,从而对节点失真数据进行重构;在此基础上,采用分布式小波数据压缩算法,根据基本的参数复制机制,在数据列、行变换的基础上做相应的递归处理,得到不同程度等级的小波系数,通过任意变换支撑长度的分布式变换,去掉环上节点内数据的时空相关性,实现节点与簇头间的分布式通信数据高效压缩。仿真结果表明,所提方法可以有效地针对不同数据进行高效压缩,处理通信数据时可以减少整体数据流参数包失误的情况发生,且具有节点能量消耗慢、压缩率高的优点。The energy of nodes in the Internet of things is limited,so it cannot support massive data transmission for a long time.In traditional data compression methods,high error rate of integrated data,low data compression rate and high energy consumption of sensor nodes are the key problems.Therefore,an efficient compression method of distributed communication data based on Internet of things was proposed.Based on the distributed structure of the Internet of things,we analyzed the boundary effect and used the wavelet function to transform the data transmitted by different nodes.According to Mallat algorithm,we calculated the low-frequency coefficient and high-frequency coefficient obtained from the data transformation,so that the node distortion data could be reconstructed.On this basis,the distributed wavelet data compression was adopted.According to the basic parameter replication mechanism,we performed the corresponding recursion based on the transformation of data column and data row,and thus to obtain the wavelet coefficients in different levels.Through the distributed transformation based on arbitrary change of support length,we removed the spatial-temporal correlation of data in the ring.Thus,we achieved the efficient compressionfor distributed communication data between the node and the cluster head.Simulation results show that the proposed method can compress different data efficiently and reduce the occurrence of parameter packet errors in the whole data stream when processing the communication data.Meanwhile,the proposed method has the advantages of low node energy consumption and high compression ratio.

关 键 词：边界效应 数据压缩 小波压缩 压缩变换 

分 类 号：TJ810.376[兵器科学与技术—武器系统与运用工程]