传感器网络中基于过滤的概率Skyline查询算法

Filter-Based Probabilistic Skyline Query Processing Algorithm in Wireless Sensor Network

针对感知数据固有的不确定性问题,研究了无线传感器网络中概率Skyline查询的处理与优化技术.首先分析了概率Skyline查询的性质,证明了概率Skyline查询的不可分解性,因而无法直接利用网内计算方法求解;进而提出了无线传感器网络中基于过滤的概率Skyline查询处理算法(filter-based probabilistic Skyline query processing algorithm in WSN,FPSP).FPSP算法将感知数据划分为候选数据、相关数据和无关数据;只需要候选数据和相关数据即可求得概率Skyline查询结果,可以在传感器节点过滤无关数据以避免大量的数据网内传输.仿真实验结果表明,FPSP算法可以有效降低传感器节点的数据传输量,极大地延长了无线传感器网络的使用寿命.

Due to the inherent uncertainty of sensing data,the processing and optimization techniques for probabilistic Skyline（PS） in wireless sensor networks（WSNs） were investigated.It has been proved that PS was not decomposable after analyzing its properties,so in-network aggregation techniques could not be used directly to improve the performance.Therefore,a filterbased probabilistic Skyline query processing algorithm in WSNs（FPSP） was proposed to evaluate the PS query in WSNs.The sensing data were divided into candidate data（CD）,relevant data（RD）,and irrelevant data（ID） by the proposed FPSP.The ID in each sensor node could be filtered directly so as to reduce data transmission cost,since PS result could be correctly obtained only according to CD and RD on the base station.The experimental results showed that most of the unnecessary data can be effectively filtered and the lifetime of WSNs can be greatly prolonged by the proposed FPSP algorithm.