基于分簇的近似KNN的查询优化算法

Approximate KNN Optimizing Queries Algorithm Based on Clustering

针对无线传感器网络查询过程消耗较多能量的情况,提出考虑位置的数据查询算法。算法首先提出位置-数据分簇算法,利用节点的地理位置信息降低向存储节点传输数据消耗的能量,由于簇之间的测量范围有重叠问题,提出基于数据离散度的查询个数分配原则,将提出的近似KNN查询优化算法与Na6ve算法、KVC算法比较,仿真结果表明,提出的算法具有更低的平均传包率,提高了网络的生存时间。

To solve the problem that the query process consumes more energy in wireless sensor networks,a location-aware KNN value query algorithm is proposed,and a locationvalue clustering algorithm is proposed which employs the location information to reduce the node energy consumption of nodes during transmission. Because the measuring range between clusters will overlap,a principle to determine the query number is proposed. Simulation results showthat in comparison with the Na6ve algorithm and kVC algorithm,the proposed algorithm has lower average rate of transmission packet and longer network lifetime.