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作 者:唐艳娜[1] 于爱华 孙桂萍[1] TANG Yanna;YU Aihua;SUN Guiping(Science and Information Science College,Qingdao Agricultural University,Qingdao 266109,China)
机构地区:[1]青岛农业大学理学与信息科学学院,山东青岛266109
出 处:《测试技术学报》2023年第5期394-399,共6页Journal of Test and Measurement Technology
摘 要:为了分析数据包节点能量消耗,精准监测无线传感网络节点的剩余能量,提出基于时间序列的节点剩余能量监测方法。构建自回归滑动平均(ARMA)时间序列分析模型,利用该模型融合无线传感网络数据,通过能量优先的原则选取出簇头,簇头运用多跳方式传递已融合的数据,并获取簇头到基站能量消耗的最佳路径;不考虑簇头节点由休眠至再次被启动的能量消耗,计算无线传感网络信息传递能耗以及簇头节点在转换自身状态时的能量消耗,只监控正常情况下网络节点传递融合信息过程中的能量消耗,监测无线传感网络节点剩余能量。结果证明该方法能有效融合网络中的数据,可实现无线传感网络节点剩余能量实时精确监测。In order to analyze the energy consumption of packet nodes and accurately monitor the residual energy of wireless sensor network nodes,a time series-based method for monitoring the residual energy of nodes is proposed.The ARMA time series analysis model is constructed,which is used to fuse the wireless sensor network data.The cluster head is selected by the principle of energy priority.The cluster head uses the multi-hop method to transmit the fused data,and obtains the best energy consumption path from the cluster head to the base station;The energy consumption of cluster head nodes from sleep to restart is not considered.The energy consumption of wireless sensor network information transmission and the energy consumption of cluster head nodes when changing their own state are calculated.Only the energy consumption of network nodes in the process of transmitting fusion information under normal conditions is monitored,and the residual energy of wireless sensor network nodes is monitored.Experiments show that this method can effectively fuse the data in the network,and can realize the real-time,intuitive and accurate monitoring of the residual energy of wireless sensor network nodes.
关 键 词:时间序列 无线传感网络 剩余能量 ARMA模型 数据融合 多跳分簇
分 类 号:TP399[自动化与计算机技术—计算机应用技术]
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