作　　者： ; ; ; ; ;

机构地区： 华南农业大学信息学院

出　　处： 《农业机械学报》 2009年第12期169-176,共8页

摘　　要： 在分析现有无线传感器查询算法基础上,借鉴了数据融合树以及位置辅助查询的思想,提出一种基于精细化梯度的能量有效动态水分传感器网络查询算法EEQA-FGG。EEQA-FGG包含了查询路由生成、查询执行流程及查询异常处理3个算法的详细设计,同时模拟分析了不同规模下区域和全网查询运行情况,并与融合树、位置辅助等方案进行了比较。仿真显示,EEQA-FGG算法可以有效降低网络能耗、均匀网络负载、延长网络生命周期,尤其在区域查询中,EEQA-FGG的生命周期可比SPT和Compass方案延长10%-50%,特别适合大规模农田监测数据查询方案。 On the basis of the existing query algorithms in wireless sensor networks, with the target to extend the life cycle, the energy-efficient query algorithms for moisture sensor networks based on finegrain gradient （EEQA - FGG） was proposed by binding the excellent idea of the aggregation tree with location-assisted querying. Further more, three sub-modules of EEQA - FGG about query routing, query processing, and query unconventionality processing were designed in detail. The EEQA - FGG in regional query and whole network query from small to ultra-large-scale network was simulated, and was compared with aggregation tree query and location-assisted query. Simulation shows that EEQA- FGG can effectively reduce energy consumption, uniform network load and extend network life cycle, and it is especially suitable for large-scale farmland monitoring data query. Particularly in regional query, the life cycle of EEQA- FGG is longer than SPT querying and Compass querying by 10% to 50%.

关 键 词： 水分 无线传感器网络 数据查询 精细化梯度

领　　域： [农业科学] [自动化与计算机技术] [自动化与计算机技术]