一种误差可控传输均衡的WSN数据融合算法

发布时间：2018-04-13 20:09

本文选题：无线传感器网络 + 传输抑制　；参考：《电子学报》2014年06期

【摘要】：如何有效降低WSN(Wiretess Sensor Net work)网内数据传输量,延长WSN的寿命,是WSN领域的研究热点.在分簇WSN基础上,实现了一种误差实时可控的数据融合算法.通过该算法,节点可自行根据近期采集的历史数据实时调整传输阈值,不同节点可保持接近的数据传输率,实现均匀耗电;自适应的阈值可以有效控制数据融合的误差.理论分析与仿真实验表明,该算法能够保证不同节点数据传输的公平性;在数据传输率相同的情况下,其求和查询及均值查询的平均绝对误差均远低于当前优秀的基于伯努利采样的数据融合方法.此算法无需先验知识,在多种WSN应用场景中具有较强的可用性与适应性.
[Abstract]:How to effectively reduce the amount of data transmission in WSN(Wiretess Sensor Net network and extend the lifetime of WSN is a hot research topic in the field of WSN.On the basis of clustering WSN, a real-time data fusion algorithm with controllable error is implemented.Through this algorithm, the node can adjust the transmission threshold in real time according to the historical data collected recently, the different nodes can maintain the close data transmission rate and realize the uniform power consumption, and the adaptive threshold can effectively control the error of data fusion.The theoretical analysis and simulation results show that the algorithm can guarantee the fairness of data transmission between different nodes, and at the same data transmission rate,The average absolute error of summation query and mean query is much lower than that of Bernoulli sampling based data fusion method.This algorithm has strong usability and adaptability in many WSN application scenarios without prior knowledge.
【作者单位】：北京邮电大学网络与交换技术国家重点实验室;
【基金】：教育部新世纪优秀人才支持计划(No.NCET100263) 教育部博士点基金(No.20110005130001) 国家高技术研究发展(863)(No.2011AA01A102) 国家自然科学基金(No.61272521)
【分类号】：TP212.9;TN929.5

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