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Improved Multi-Dimensional Top-K Query Processing Based on Data Prediction in Wireless Sensor Networks

並列摘要


Since the scale of wireless sensor networks is expanding and one single node can sense a variety of data, selecting the data of interest to users from a tremendous data stream has become an important topic. With further development in the field of WSN query, extensive research is being conducted to solve different kinds of query issues. Skyline is a typical query for multi-criteria decision making, and many applications have been developed for it. Studies of multi-dimensional top-k query processing have proven it to be more efficient than traditional centralized scheme. In some cases, variations of observed conditions, such as temperature and humidity, are related to time. Thus, we used a data-prediction method to establish the bi-boundary filter rule, which helps filter the data that may be dropped by the sets of final result. The bi-boundary filter rule determines whether the received or generated data will be transmitted. We analyzed the simulation results and concluded that the bi-boundary filter rule can be more energy-efficient in situations in which a temporal correlation exists.

並列關鍵字

WSNs Top-k Data filter

被引用紀錄


陳宏源(2015)。藍牙定位網之硬體模型佈建研究〔碩士論文,淡江大學〕。華藝線上圖書館。https://doi.org/10.6846/TKU.2015.00485
劉建志(2015)。藍牙定位演算法之評估研究〔碩士論文,淡江大學〕。華藝線上圖書館。https://doi.org/10.6846/TKU.2015.00459
陳彥銘(2016)。輕量化低成本全向式雷射測距儀設計與實作〔碩士論文,國立虎尾科技大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0028-1108201601294000

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