中文摘要：

无线传感器网络中传感器的能量有限,怎样节约能量延长传感器的寿命,是无线传感器研究网络研究中的重要问题。数据融合作为无线传感器网络的关键技术之一,它的作用体现在减少数据的上传量,提高数据准确性,节省能量等方面。研究传感器节点收集到的大量数据,发现数据满足周期性,提出了基于时间周期的数据融合算法。在融合算法中根据历史数据基于拉格朗日插值法的预测算法预测未来数据,设置误差阈值来检测预测数据。室外温度数据满足文章研究的条件,因此基于时间周期的无线传感器网络数据融合算法以沈阳地区夏天温度数据为样本,用Matlab进行仿真实验对该算法进行了验证,实验结果表明该算法减少了传输的数据量,节约了节点的能量,延长了网络的寿命。

英文摘要：

Since the energy of sensors is limited in wireless sensor networks,it is an important problem that how to save energy and extend the life of sensors.As one of the key technologies,data fusion could reduce the amount of data uploaded,improve data accuracy,and save energy.Studying the data sensors collected,we found that the data is periodic,thus we proposed data fusion algorithm based on time period.In the data fusion algorithm,we use Lagrange interpolation method to predict future data.To detect forecast data,we set threshold value.Because outdoor temperature data meets the conditions,we use Shenyang summer temperature data for sample,and we use matlab simulation experiment to verify the algorithm.Experimental results show that the algorithm reduces the amount of data uploaded,save the energy of the node,and extend the life of network.