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In-Network Execution of Monitoring Queries in Sensor Networks

机译:传感器网络中监视查询的网络内执行

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Sensor networks are widely used in many applications for collecting information from the physical environment. In these applications, it is usually necessary to track the relationships between sensor data readings within a time window to detect events of interest. However, it is diffcult to detect such events by using the common aggregate or selection queries. We address the problem of processing window self-join in order to detect events of interest. Self-joins are useful in tracking correlations between different sensor readings, which can indicate an event of interest. We propose the Two-Phase Self-Join (TPSJ) scheme to efficiently evaluate self-join queries for event detection in sensor networks. Our TPSJ scheme takes advantage of the properties of the events and carries out data filtering during in-network processing. We discuss TPSJ execution with one window and we extend it for continuous event monitoring. Our experimental evaluation results indicate that the TPSJ scheme is eective in reducing the amount of radio transmissions during event detection.
机译:传感器网络广泛用于许多应用程序中,以从物理环境中收集信息。在这些应用中,通常有必要在一个时间窗口内跟踪传感器数据读数之间的关系,以检测感兴趣的事件。但是,很难通过使用公共聚合或选择查询来检测此类事件。我们解决了处理窗口自连接以便检测感兴趣事件的问题。自联接在跟踪不同传感器读数之间的相关性时很有用,这可以指示感兴趣的事件。我们提出了两阶段自连接(TPSJ)方案,以有效地评估用于传感器网络中事件检测的自连接查询。我们的TPSJ方案利用事件的属性,并在网络内处理期间执行数据过滤。我们用一个窗口讨论TPSJ执行,并将其扩展为连续事件监视。我们的实验评估结果表明,TPSJ方案有效地减少了事件检测过程中的无线电传输量。

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