Dynamic Optimization Method of Wireless Network Routing Based on Deep Learning Strategy

• Published in: Mobile information systems 2022-07, Vol.2022, p.1-11
• Main Authors: Wang, Pengjun, Qin, Jiahao, Li, Jiucheng, Wu, Meng, Zhou, Shan, Feng, Le
• Format: Article
• Language: English
• Subjects: Algorithms; Computer simulation; Data processing; Deep learning; Dynamic programming; Embedded systems; Energy consumption; Energy efficiency; Energy utilization; Machine learning; Network management systems; Neural networks; Optimization; Route optimization; Routing (telecommunications); Satellite communications; Sensors; Wireless networks; Wireless sensor networks
• ISSN: 1574-017X; 1875-905X
• DOI: 10.1155/2022/4964672

Wireless sensor network is a network that integrates sensor technology, computer technology, information processing technology, and communication technology. This paper aims to study how to analyze and study the routing optimization of wireless sensor network based on deep learning and describe the neural network. This paper puts forward the problem of routing optimization, which is based on the dynamic programming of wireless sensor network, and then elaborates around its concept and related algorithms and designs and analyzes the case of wireless sensor network optimization. Through the comparative analysis of the five algorithms in computer simulation, although the average network delay performance of DPER reached 0.47 s, it could effectively prolong the life cycle of the network. The DPER algorithm not only improves the network life but also improves the network energy utilization rate, shortens the average path length of the network, and reduces the standard deviation of the remaining energy of the node.