摘要
综合考虑了能量消耗、查询延迟、查询结果正确性等因素,提出了一种基于网格的传感器网络K近邻查询处理算法GKNN。它优化现有的查询区域估计方法以减少算法的能量消耗。利用网格对节点进行管理,将查询区域中的网格划分成多个网格区,由各个网格区并行处理查询从而减少延迟。另外,GKNN利用节点冗余降低了节点失效对查询结果的影响,提高了查询结果的正确性。仿真实验结果表明,GKNN优于现有的算法。
A grid-based KNN query processing algorithm called GKNN was proposed in this paper which takes energy consumption,query latency,query result correctness and etc into consideration in an integrated way.It optimizes the existing query area estimation methods in order to reduce the energy consumption of the algorithm.GKNN takes advantage of grids to manage the nodes and divides the query region into several grid zones.Each grid zone processes query parallel to reduce query latency.Furthermore,GKNN takes advantage of node redundancy to reduce the influence of node failures on query result correctness which improves the accuracy of query result.Experimental results show that GKNN outperforms the existing algorithms.
出处
《计算机科学》
CSCD
北大核心
2011年第5期31-36,共6页
Computer Science
基金
国家自然科学基金资助项目(60673127)
国家高技术研究发展计划("863"计划)基金资助项目(2007AA01Z404)
江苏省科技支撑计划(BE2008135)
工信部电子信息产业发展基金项目资助
