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Analysis of efficient Optimization Algorithm for Chaotic Information Nodes in Wireless Networks
Author(s) -
Jing Qiu
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/750/1/012238
Subject(s) - computer science , wireless network , key distribution in wireless sensor networks , wireless sensor network , chaotic , node (physics) , computer network , wireless , quantization (signal processing) , wireless wan , hidden node problem , wi fi array , real time computing , algorithm , engineering , artificial intelligence , telecommunications , structural engineering
Aiming improve the ability of fault detection and diagnosis of wireless network communication, the network chaotic information nodes are detected accurately and efficiently. An efficient detection method for chaotic information nodes in wireless networks is proposed based on quantization tracking and identification of sensor information. Firstly, the node connectivity graph model of wireless network communication is constructed, the link transmission channel of wireless network communication is analyzed, and the topology structure of distributed node is designed. Then the distributed sensor detection technique is used to detect the node output link equalization of wireless network communication. The higher-order spectral features of the output bit sequence stream of wireless network communication channel are extracted, and the anomaly of the characteristic quantity is extracted according to the characteristic quantity. The sensor information quantization tracking and identification technology is used to detect the chaotic information nodes in wireless network. Finally, the simulation test of high efficiency optimization detection of chaotic information nodes in wireless network communication is carried out. The results show that the accuracy of efficient optimization detection for chaotic information nodes is high by using this method. The quality of wireless network communication is improved because of the good real-time performance of network interrupt detection and fault diagnosis.

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