利用联合图模型的传感器网络数据修复方法

doi:10.19665/j.issn1001-2400.2020.01.007

Abstract

Abstract:

In order to ensure that the sensor network data are reliable, and that the efficiency of data processing is not reduced due to the lack of network data, a method for data recovery in the sensor network based on the joint graph model is proposed. First, this paper establishes a joint graph domain model based on the smoothness of network data in the time-domain and spatial-domain, and then an iterative recovery method is proposed to recover the network data, which is based on the association characteristics of network data in the joint graph domain model. Experimental simulation shows that compared with the recovery method based on graph total variation minimization in the graph signal model, the method of data recovery based on the joint graph model improves not only by about thirty percent of the data recovery accuracy, but also by about eighty percent of the iteration efficiency.

Key words: wireless sensor networks, data recovery, graph signal processing, joint graph model

CLC Number:

TN911.7

YANG Jie,JIANG Junzheng. Method for data recovery in the sensor network based on the joint graph model[J].Journal of Xidian University, 2020, 47(1): 44-51.

Figures/Tables 6

References 16

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丢失比例 /%	均方根误差		迭代次数
丢失比例 /%	文中算法	GTVM	文中算法	GTVM
30	1.45	2.12	90.43	187.21
40	1.77	2.55	121.34	322.95
50	2.11	2.96	162.22	666.80
60	2.45	3.37	229.07	1576.04
70	2.83	3.86	361.58	5432.41
80	3.26	4.43	641.79	16895.16
90	3.98	5.38	2019.54	54009.75

丢失比例 /%	均方根误差		迭代次数
丢失比例 /%	文中算法	IHT-GS	文中算法	IHT-GS
30	1.00	0.93	90.55	94989.02
40	1.26	5.28	118.97	100000
50	1.51	12.78	160.00	100000
60	1.81	22.01	231.36	100000
70	2.13	34.06	361.30	100000
80	2.51	48.06	630.21	97659.28
90	3.16	62.22	2727.83	25625.24

丢失比例 /%	均方根误差		迭代次数
丢失比例 /%	文中算法	GTVM	文中算法	GTVM
30	0.47	0.67	70.03	133.99
40	0.58	0.84	91.19	225.85
50	0.71	1.06	131.4	440.07
60	0.86	1.32	194.2	994.79
70	1.05	1.67	301.7	2654.68
80	1.32	2.16	508.0	7316.90
90	1.78	2.95	1426.7	21124.05

丢失比例 /%	均方根误差		迭代次数
丢失比例 /%	文中算法	IHT-GS	文中算法	IHT-GS
30	0.37	0.02	69.35	30634.98
40	0.46	0.27	91.03	77086.53
50	0.58	1.59	121.69	99912.16
60	0.72	4.99	175.50	100000
70	0.90	9.57	264.63	99631.05
80	1.18	13.46	475.67	67299.48
90	1.77	17.04	2397.73	5196.93

Method for data recovery in the sensor network based on the joint graph model

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