In recent years, sensor technology has attracted the attention of countries all over the world because of its potential huge application value, and it has played an important role in people's daily life and social production activities. This paper mainly studies the location algorithm based on ranging in the location algorithm and analyzes the advantages and disadvantages of the algorithm. In order to optimize the positioning of wireless sensor networks, a fuzzy controller is designed to fuzzify the input information of sensor nodes. Using Matlab network simulation tool, the congestion control algorithm proposed in this paper was simulated and compared with several typical congestion control protocols in wireless sensor networks. Experimental results show that the algorithm can improve network throughput, reduce network packet loss, and have a significant impact on network performance. The network throughput of the congestion control algorithm based on fuzzy logs is stable at 180 packets per second. Compared with CODA, the congestion control algorithm based on fuzzy logarithm increases the packet loss rate by 55–66%, and the SenTCP algorithm increases by 37–40%. It can be seen that congestion control algorithms based on fuzzy logic can play an important role in wireless sensor networks.

中文翻译：

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节点模糊识别与定位在无线传感器网络中的研究与应用

近年来，传感器技术因其潜在的巨大应用价值引起了世界各国的关注，在人们的日常生活和社会生产活动中发挥了重要作用。本文主要研究了定位算法中基于测距的定位算法，并分析了该算法的优缺点。为了优化无线传感器网络的定位，设计了模糊控制器对传感器节点的输入信息进行模糊化处理。利用Matlab网络仿真工具，对本文提出的拥塞控制算法进行了仿真，并与无线传感器网络中几种典型的拥塞控制协议进行了比较。实验结果表明，该算法能够提高网络吞吐量，减少网络丢包，并对网络性能产生重大影响。基于模糊日志的拥塞控制算法网络吞吐量稳定在180包/秒。与CODA相比，基于模糊对数的拥塞控制算法丢包率提高了55-66%，SenTCP算法提高了37-40%。可见，基于模糊逻辑的拥塞控制算法在无线传感器网络中可以发挥重要作用。