scholarly journals A Dynamic Variance-Based Triggering Scheme for Distributed Cooperative State Estimation over Wireless Sensor Networks

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Hongbo Zhu ◽  
Jiabao Ding
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
State Estimation ◽  
Wireless Channel ◽  
Wireless Sensor ◽  
Estimation Accuracy ◽  
Time Interval ◽  
Dynamical Process ◽  
Distributed Sensors ◽  
Stochastic Dynamical System

Wireless sensor networks (WSNs) have been spawning many new applications where cooperative state estimation is essential. In this paper, the problem of performing cooperative state estimation for a discrete linear stochastic dynamical system over wireless sensor networks with a limitation on the sampling and communication rate is considered, where distributed sensors cooperatively sense a linear dynamical process and transmit observations each other via a common wireless channel. Firstly, a novel dynamic variance-based triggering scheme (DVTS) is designed to schedule the sampling of each sensor and the transmission of its local measurement. In contrast to the existing static variance-based triggering scheme (SVTS), the newly proposed DVTS can lead to the larger average intertrigger time interval and thus fewer total triggering number with almost approximate estimation accuracy. Second, a new Riccati equation of the prediction variance iteration for each estimator is obtained, which switches dynamically among the modes related to the variance of the previous step and the recently received measurements from other sensors. Furthermore, the stability issue is also mainly investigated. Finally, simulation results show the effectiveness and advantage of the proposed strategy.

Energy-efficient routing sensing technology of wireless sensor networks based on Internet of Things

2021 ◽  
Vol 27 (3) ◽  
pp. 225-235
Author(s):  
Xiaotao Ju
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Cluster Head ◽  
Energy Performance ◽  
Wireless Channel ◽  
Wireless Sensor ◽  
Duty Ratio ◽  
Support Vector ◽  
Energy Efficient Routing

This research was conducted to enhance the energy performance of wireless sensor networks (WSN) and improve the performance of end-to-end delay and packet receiving rate of network operation. In this study, the low-energy data collection routing algorithm and adaptive environment sensing method in WSN were mainly examined. The node centrality, energy surplus, and node temperature were calculated for cluster head selection to reduce the energy consumption of nodes and improve the reliability of network data. The research results have shown that the parameter setting guided by the theoretical analysis makes each node selfishly achieve the maximum expected benefit while the whole network runs reliably, and the energy consumption is reduced by the selfishness of the node. As a result, the proposed algorithm can effectively reduce the network energy consumption and increase the network life cycle of wireless sensor networks. It can be seen that the machine learning methods such as support vector machine are used to model and analyze the state of the sensing node, and to obtain more accurate wireless channel availability judgment based on the historical state data, thereby adaptively adjusting the working duty ratio and reducing the invalidity data sent.

scholarly journals An efficient cryptographic technique using modified Diffie–Hellman in wireless sensor networks

2020 ◽  
Vol 16 (6) ◽  
pp. 155014772092577 ◽  
Author(s):  
Shahwar Ali ◽  
A Humaria ◽  
M Sher Ramzan ◽  
Imran Khan ◽  
Syed M Saqlain ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Security ◽  
Response Times ◽  
Base Station ◽  
Wireless Channel ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Key Generation ◽  
Diffie Hellman

In wireless sensor networks, the sensors transfer data through radio signals to a remote base station. Sensor nodes are used to sense environmental conditions such as temperature, strain, humidity, sound, vibration, and position. Data security is a major issue in wireless sensor networks since data travel over the naturally exposed wireless channel where malicious attackers may get access to critical information. The sensors in wireless sensor networks are resource-constrained devices whereas the existing data security approaches have complex security mechanisms with high computational and response times affecting the network lifetime. Furthermore, existing systems, such as secure efficient encryption algorithm, use the Diffie–Hellman approach for key generation and exchange; however, Diffie–Hellman is highly vulnerable to the man-in-the-middle attack. This article introduces a data security approach with less computational and response times based on a modified version of Diffie–Hellman. The Diffie–Hellman has been modified to secure it against attacks by generating a hash of each value that is transmitted over the network. The proposed approach has been analyzed for security against various attacks. Furthermore, it has also been analyzed in terms of encryption/decryption time, computation time, and key generation time for different sizes of data. The comparative analysis with the existing approaches shows that the proposed approach performs better in most of the cases.

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