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Research of WSN Localization Algorithm Based on Entropy Function

机译:基于熵函数的WSN定位算法研究

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Sensor networks are composed of large numbers of sensors that are equipped with a processor, memory, wireless communication capabilities, sensing capabilities and a power source (battery) on board. While in most existing sensor networks, sensors are static, some modern applications involve sensors that are mobile. Most existing localization algorithms were designed to work well either in networks of static sensors or networks in which all sensors are mobile. However, these existing sensor nodes localization schemes assume a benign environment, where all sensor nodes are supposed to provide correct reference information. When the sensor networks are deployed in a hostile environment, where sensor nodes can be compromised, such an assumption does not hold anymore. In this paper, we propose an new WSN localization algorithms, which based on the entropy function. It is different from the existing localization algorithms, which is an improvement algorithm. In many complex environment, such as pressure field, temperature field and magnetic field etc, we can use this localization scheme to localize sensor nodes, and results show that its performance is well.
机译:传感器网络由大量传感器组成,这些传感器配备了处理器,内存,无线通信功能,传感功能和板上电源(电池)。虽然在大多数现有的传感器网络中,传感器是静态的,但某些现代应用程序涉及可移动的传感器。大多数现有的本地化算法都设计为在静态传感器网络或所有传感器都可移动的网络中很好地工作。但是,这些现有的传感器节点定位方案假定为一个良性环境,在该环境中,所有传感器节点都应提供正确的参考信息。当传感器网络部署在可能会损害传感器节点的敌对环境中时,这种假设将不再成立。本文提出了一种新的基于熵函数的无线传感器网络定位算法。它不同于现有的定位算法,后者是一种改进算法。在许多复杂的环境中,例如压力场,温度场和磁场等,我们可以使用这种定位方案对传感器节点进行定位,结果表明其性能良好。

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