A Recovery Method of Data Lost in Network Communication

Author(s):  
Bo Zhang ◽  

At present, ScanDisk is used to recover the data lost in network communication. But this method is limited in scope, and once the lost data is covered, it’s difficult or impossible to recover it, which results in low recovery degree. Accordingly, a recovery method for lost data in network communication based on RAID6 is proposed. Firstly, according to the mechanism of data loss in network communication, the missing data is divided into three categories: random loss, completely random loss and nonrandom loss, and then according to the results of classification, the recovery problem of the data loss in network communication is converted into the problem of matrix completion, finally, a low-rank decomposition model is proposed, according to the low rank characteristics of the matrix, the lost data in the matrix is recovered, thus the recovery of the lost data in network communication is finished. Experimental results show that the proposed method can easily recover the lost data in network communication with a simple operation, low computing complexity and strong applicability, and can be used as a universal recovery method for data lost in network communication.

2018 ◽  
Vol 20 (10) ◽  
pp. 2659-2669 ◽  
Author(s):  
Jiandong Tian ◽  
Zhi Han ◽  
Weihong Ren ◽  
Xiai Chen ◽  
Yandong Tang

2017 ◽  
Vol 19 (5) ◽  
pp. 969-983 ◽  
Author(s):  
Hengyou Wang ◽  
Yigang Cen ◽  
Zhihai He ◽  
Ruizhen Zhao ◽  
Yi Cen ◽  
...  

2017 ◽  
Vol 21 (2) ◽  
Author(s):  
Tatiana Gelvez ◽  
Hoover Rueda ◽  
Henry Arguello

<p>Spectral imaging aims to capture and process a 3-dimensional spectral image with a large amount of spectral information for each spatial location. Compressive spectral imaging techniques (CSI) increases the sensing speed and reduces the amount of collected data compared to traditional spectral imaging methods. The coded aperture snapshot spectral imager (CASSI) is an optical architecture to sense a spectral image in a single 2D coded projection by applying CSI. Typically, the 3D scene is recovered by solving an L1-based optimization problem that assumes the scene is sparse in some known orthonormal basis. In contrast, the matrix completion technique (MC) allows to recover the scene without such prior knowledge. The MC reconstruction algorithms rely on a low-rank structure of the scene. Moreover, the CASSI system uses coded aperture patterns that determine the quality of the estimated scene. Therefore, this paper proposes the design of an optimal coded aperture set for the MC methodology. The designed set is attained by maximizing the distance between the translucent elements in the coded aperture. Visualization of the recovered spectral signals and simulations over different databases show average improvement when the designed coded set is used between 1-3 dBs compared to the complementary coded aperture set, and between 3-9 dBs compared to the conventional random coded aperture set.</p>


Author(s):  
Chen Chen ◽  
Baochang Zhang ◽  
Alessio Del Bue ◽  
Vittorio Murino

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