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Research and application of node fuzzy identification and localization in wireless sensor networks

机译:节点模糊识别与定位在无线传感器网络中的研究与应用

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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.
机译:近年来,由于其潜在的巨大应用价值,传感器技术引起了世界各国的关注,在人们日常生活和社会生产活动中发挥了重要作用。本文主要研究了基于定位算法的范围的位置算法,分析了算法的优点和缺点。为了优化无线传感器网络的定位,模糊控制器被设计为模糊传感器节点的输入信息。使用MATLAB网络仿真工具,模拟了本文提出的拥塞控制算法,并与无线传感器网络中的几种典型拥塞控制协议进行了模拟。实验结果表明,该算法可以提高网络吞吐量,降低网络数据包丢失,对网络性能产生重大影响。基于模糊日志的拥塞控制算法的网络吞吐量在每秒180个包中稳定。与Coda相比,基于模糊对数的拥塞控制算法将丢包率提高55-66%,并且SentCP算法增加了37-40%。可以看出,基于模糊逻辑的拥塞控制算法可以在无线传感器网络中发挥重要作用。

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