scholarly journals Impact of physical layer design on the deployment of a sensor network with correlated observations

Author(s):  
T. Banerjee ◽  
A. A. Kherani ◽  
M. Debbah ◽  
A. Roumy
2012 ◽  
Vol 220-223 ◽  
pp. 1871-1876
Author(s):  
Feng Mei Liang ◽  
Bin Liu

Due to energy restrictions, node distribution density and hardware computing power etc., the traditional time synchronization mechanism is not suitable for wireless sensor network. The paper discussed the main reason that caused asynchronization and proposed an improved time synchronization algorithm based on cross layer optimization for wireless sensor network. Considering the stability of crystal oscillation and the linearity of crystal deviation in the physical layer, the improved time synchronization mechanism implemented a self-correction by the cross-layer MAC protocol. Estimating the crystal oscillation drift, the crystal deviation had been self-corrected just by a few times data broadcast. The experiment on the MCU Si1000 physical layer platform has demonstrated the practicability of the algorithm. The synchronization algorithm is able to keep a stable network operation in the way of extending the synchronization period and reducing the synchronization cost. The synchronization mechanism is applicable to the active acquisition network, especially the realtime one.


In recent years, wireless sensor network (WSN) is the measure concern over network communication. A number of attacks are occurred at the time of network communication as result it hampers the smooth functionality, data flow and data transmission. In this article, we have proposed a trust-based intrusion detection system for physical layers attacks using DRI and Cross Check method. The HTBIDS is effective method to identify the abnormal nodes in wireless sensor network. The abnormal nodes are attacked by periodic jamming attack. We have considered the periodic jamming attack at physical layer for performance evaluation. Results show that HTBIDS performs better using detection accuracy (DA) and false alarm rate (FAR).


Author(s):  
Jae-Yong Lee ◽  
Suhada Jayasuriya

This paper presents a concept and its application of the dynamic multi-layered sensor network for gathering environment information. The architecture of the system is composed of sensor layer, physical layer, and communication layer. Sensor layer is the combination and the network of the sensor components in each sensor node. A sensor node has multiple numbers of sensors, and a number of robots for the mobile sensor network. Each mobile robot plays a role of mobile base for a sensor node, and consists of physical layer. We discuss the formation of the multi-layered sensor network, which is active, adaptive, and task oriented in the surrounding environment. As each sensor node consists of multiple numbers of heterogeneous sensors, sensor combination is not restricted to one particular objective or task. This fact allows the network to be multi-functional. Same kind of sensors can establish ad-hoc sensor network, while different kind of sensors fuse the data for improved interpretation of the environment. Experiments with mobile sensors nodes are conducted and illustrated to show the concept of the multi-layered mobile sensor network.


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