Research on WSN for IoT device collaboration based on path quality and federated learning
This study proposes a novel routing mechanism based on path quality and federated learning to address the stability and reliability issues of wireless sensor networks(WSN)during data transmission.This mechanism comprehensively considers key indicators such as signal strength,latency,and packet loss rate,and achieves data privacy protection between devices and collaborative training of global models through federated learning algorithms.The experimental results show that the new routing mechanism achieves a success rate of 95.8%in data transmission,reduces the average energy consumption of nodes to 2.0 joules,and extends the network lifetime to a maximum of 320 rounds,significantly better than traditional routing mechanisms.In addition,the introduced node energy balance strategy further optimizes the energy consumption distribution,providing a guarantee for the long-term stable operation of WSN.
万方数据
维普
