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Optimizing evaluation patterns and data acquisition for stream analytics in resource-constrained wireless environments

机译:在资源受限的无线环境中优化评估模式和数据采集以进行流分析

摘要

Mobile wireless devices may receive data streams from multiple remote sensors. The sensors may have limited power supplies and memory capacity. Aspects of the invention use statistical characteristics of the sensor data streams and the cost of acquiring a single element of each stream to determine what sequence the sensors should send their data streams in. The cost of acquiring the data may be modified dynamically, depending on parameters such as block size. Additional factors, such as a sensor's buffer capacity, may limit the amount of stream elements that may be cached and affect the sensors' stream transmit sequence. The evaluation order may be dynamically modified using an event processing engine, to reflect both changing statistics of underlying sensor stream tuples and time-varying acquisition costs associated with individual streams. This helps to increase in the operational lifetime of the sensors and associated monitoring applications.
机译:移动无线设备可以从多个远程传感器接收数据流。传感器的电源和内存容量可能有限。本发明的各方面使用传感器数据流的统计特性以及获取每个流的单个元素的成本来确定传感器应以什么顺序发送其数据流。可以根据参数来动态地修改获取数据的成本。例如区块大小。其他因素(例如传感器的缓冲容量)可能会限制可能缓存的流元素的数量,并影响传感器的流传输顺序。可以使用事件处理引擎动态修改评估顺序,以反映基础传感器流元组的变化统计信息以及与各个流相关联的随时间变化的获取成本。这有助于延长传感器和相关监视应用程序的使用寿命。

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