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基于精細(xì)化梯度的水分傳感器網(wǎng)絡(luò)能量高效查詢算
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-efficient Query Algorithms for Moisture Sensor Networks Based on Fine-grain Gradient
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    摘要:

    在分析現(xiàn)有無線傳感器查詢算法基礎(chǔ)上,借鑒了數(shù)據(jù)融合樹以及位置輔助查詢的思想,提出一種基于精細(xì)化梯度的能量有效動態(tài)水分傳感器網(wǎng)絡(luò)查詢算法EEQA-FGG。EEQA-FGG包含了查詢路由生成、查詢執(zhí)行流程及查詢異常處理3個算法的詳細(xì)設(shè)計(jì),同時模擬分析了不同規(guī)模下區(qū)域和全網(wǎng)查詢運(yùn)行情況,并與融合樹、位置輔助等方案進(jìn)行了比較。仿真顯示,EEQA-FGG算法可以有效降低網(wǎng)絡(luò)能耗、均勻網(wǎng)絡(luò)負(fù)載、延長網(wǎng)絡(luò)生命周期,尤其在區(qū)域查詢中,EEQA-FGG的生命周期可比SPT和Compass方案延長10%~50%,特別適合大規(guī)模農(nóng)田監(jiān)測數(shù)據(jù)查詢方案。

    Abstract:

    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 fine-grain 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%. 

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肖德琴,周權(quán),王景利,李就好,羅錫文.基于精細(xì)化梯度的水分傳感器網(wǎng)絡(luò)能量高效查詢算[J].農(nóng)業(yè)機(jī)械學(xué)報,2009,40(12):169-176.-efficient Query Algorithms for Moisture Sensor Networks Based on Fine-grain Gradient[J]. Transactions of the Chinese Society for Agricultural Machinery,2009,40(12):169-176.

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