【摘要】 为了构建传感器网络流数据的概要数据,给出了一种基于时间滑动窗口的自适应加权随机抽样算法:AWRS/BTSW算法.算法根据流数据的到达时间和变化情况,赋予流数据一定的键值,根据流数据的键值并结合skipping因子生成概要数据.在深海平台监测系统中,流数据变化不确定,算法可以根据数据的变化情况动态调整抽样方式,在数据变化不稳定的情况下,生成概要数据的准确性高;在数据变化稳定的情况下,生成概要数据的效率高.更多还原

【Abstract】 To obtain the synopsis data of the stream data from the sensor networks,an adaptive weighted random sampling algorithm,AWRS/BTSW algorithm,is provided based on time sliding window.Firstly,the algorithm assigns a key value to a stream data according to its arrival time and changes;then,based on the key value and skipping factor,the algorithm generates synopsis data.In the deep sea platform monitoring system,the change of stream data is unknown.The algorithm can dynamically adjust sampling according to data variation.If the data is stable,it generates synopsis data efficiently.Even if the data is unstable,it also generates accurate synopsis data.更多还原