Wireless Sensor Network Data Fusion Model Based on Compressed Sensing Theory

2016 ◽  
Vol 13 (12) ◽  
pp. 9515-9520 ◽  
Author(s):  
Liu Xiao ◽  
Yang Jian
Keyword(s):  
Wireless Sensor Network ◽  
Compressed Sensing ◽  
Data Fusion ◽  
Sensor Network ◽  
Wireless Sensor ◽  
Network Data ◽  
Fusion Model ◽  
Model Based

The Data Fusion Survivability Analysis Technology of Wireless Sensor Network

2013 ◽  
Vol 427-429 ◽  
pp. 2630-2635
Author(s):  
Le Jun Zhang ◽  
Xin Deng ◽  
Lin Guo ◽  
Jian Pei Zhang ◽  
Hong Bo Li
Keyword(s):  
Wireless Sensor Network ◽  
Data Fusion ◽  
Sensor Network ◽  
Petri Net ◽  
Theoretical Basis ◽  
Simulation Experiment ◽  
Wireless Sensor ◽  
Analysis Model ◽  
Fusion Model ◽  
Definition Of

This paper presents the data fusion survivability analysis model of wireless sensor network (WSN) based on stochastic Petri net (SPN). First, the definition of data fusion survivability is put forward, and the data fusion model of WSN is constructed. Second, the SPN modeling method of security events, which influences the WSN, is described. Lastly, simulation experiment proves the correctness and effectiveness of the modeling of WSN data fusion survivability analysis based on SPN. This model can provide the theoretical basis and guide for designing a survivable WSN.

Research on Data Compression of WSN Based on Compressed Sensing

2014 ◽  
Vol 686 ◽  
pp. 423-428 ◽  
Author(s):  
Jun Xia Li
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Compressed Sensing ◽  
Data Compression ◽  
Network Coding ◽  
Sensor Network ◽  
Environmental Data ◽  
Wireless Sensor ◽  
Network Data

For Wireless Sensor Networks (WSN) is responsible for sensing, collecting, processing and monitoring of environmental data, but it might be limited in resources. This paper describes in detail the compressed sensing theory, study the wireless sensor network data conventional compression and network coding method. The linear network coding scheme based on sparse random projection theory of compressed sensing. Simulation results show that this system satisfies the requirements of the reconstruction error of packets needed to reduce the number of nodes to the total number of 30%, improves the efficiency of data communications in wireless sensor network, reduce the energy consumption of the system. With other wireless sensor network data compression algorithm, the proposed algorithm has the advantages of simple realization, the compression effect is good, especially suitable for resource limited, and the accuracy requirements are not particularly stringent in wireless sensor networks.

Sign in / Sign up

Export Citation Format

Share Document