公路网上移动对象连续k近邻查询的一种方法

公路网上移动对象连续k近邻查询是最近时空数据库查询中的一个研究热点,它是在一个时间段内找到离查询点最近的K个移动对象.我们分析了现有查询方法,存在的问题主要是运动对象位置随时间而频繁变化以至于不能及时更新运动对象的信息而导致返回KNN结果不正确.为了解决这些问题,采用一种距离预计算方法,使计算量减少,从而为更新通讯获得更多时间.通过实验证明,我们提出的方法是有效的.

A Method of Continuous K-Nearest Neighbor Query over Moving Objects in Road Network

It is a recent focus to research on continuous K-Nearest Neighbor（CKNN） query over moving Objects in Road Networks on spatio-temporal database query.A CKNN query is to find among all moving objects the K-nearest neighbors（KNNs） of a moving query object at time interval.We investigated the existing query methods,the main issue remains that the location of moving objects are frequently changed over time so that moving objects can not be updated in time,thus lead to retrieve the incorrect results of KNN.In order to solve these problems,an effective method dealing with continuous K-Nearest Neighbor query is proposed,which is a distance pre-computation to reduce the cost of computation of the network distance between moving objects and q.Comprehensive experiments have proved that our proposed method is effective.