一种误差可控传输均衡的WSN数据融合算法

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。%How to effectively suppress transmissions of WSN (Wiretess Sensor Net work)and prolong its lifetime has become a hot area of research for WSN .In cluster-based WSNs ,a precision configurable data aggregation algorithm (PCDA )is proposed . Through PCDA ,every node adapts its threshold based on recent historical data so that nodes can suppress transmissions fairly ;the adaptive threshold can control the error of aggregations in real-time .Theoretical analysis and experiment results show that nodes can save energy effectively through PCDA .Compared with Bernoulli sampling based aggregation ,MAEs (Mean Absolute Errors )of con-tinuous queries of sum aggregation and average aggregation is much smaller through PCDA .Furthermore ,PCDA needs no future knowledge ,making it usable and adaptive in many WSN applications .