一种无线传感器网络静态节点分类算法设计

A Static Node Classification Algorithm Design for a Wireless Sensor Network

传感器网络中产生大量的原始数据需要通过有限的带宽传输到中央节点进行处理,且这些数据中高频信号可能容易受到噪声和干扰的影响,导致数据质量下降,影响分类效率和质量。对此,提出一种无线传感器网络静态节点分类算法。对无线传感器网络静态节点数据滤波,描述静态节点属性特征;利用场可编程门阵列(Field Programmable Gate Array,FPGA)实现传感器节点的数字下变频,降低信号频率,进一步减少噪声和干扰对信号的影响,并减少数据的传输量;引入支持向量机算法,完成静态节点的分类。实验证明,该算法可以在短时间内完成大量的数据处理任务,分类效果好,具有应用价值。

A large amount of raw data generated in the sensor network needs to be transmitted to the central node through limited bandwidth for processing,and the high-frequency signals in these data may be vulnerable to noise and interference,leading to the decline of data quality and affecting the classification efficiency and quality.A static node classification algorithm of wireless sensor network is proposed in the paper.Data filtering of wireless sensor network uses FPGA to reduce signal frequency,further reduce the influence of noise and interference on signal,and decrease the amount of data transmission.Supporting feature machine algorithm is introduced to complete the classification of static nodes.Experiments show that the algorithm can complete a large number of data processing tasks in a short time,with good classification effect and good application value.