Optimizing evaluation patterns and data acquisition for stream analytics in resource-constrained wireless environments
    1.
    发明授权
    Optimizing evaluation patterns and data acquisition for stream analytics in resource-constrained wireless environments 有权
    在资源有限的无线环境中优化流分析的评估模式和数据采集

    公开(公告)号:US09137282B2

    公开(公告)日:2015-09-15

    申请号:US14081308

    申请日:2013-11-15

    Abstract: 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.

    Abstract translation: 移动无线设备可以从多个远程传感器接收数据流。 传感器可能具有有限的电源和存储容量。 本发明的各方面使用传感器数据流的统计特征和获取每个流的单个元素的成本来确定传感器应该发送其数据流的顺序。获取数据的成本可以根据参数动态地修改 如块大小。 附加因素,如传感器的缓冲区容量,可能会限制可能被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来动态地修改评估顺序,以反映底层传感器流元组的变化的统计信息和与各个流相关联的时变获取成本。 这有助于增加传感器和相关监控应用的使用寿命。

    Method and System for Improving Personal Productivity in Home Environments
    2.
    发明申请
    Method and System for Improving Personal Productivity in Home Environments 审中-公开
    提高家庭环境中个人生产率的方法与系统

    公开(公告)号:US20140080106A1

    公开(公告)日:2014-03-20

    申请号:US14084934

    申请日:2013-11-20

    CPC classification number: G09B19/00 G06N5/04 G06N20/00 G06Q30/02

    Abstract: Method and system for improving personal productivity in home environments may store state information associated with an environment and one or more users in a knowledge base, detected activity of a user, infer location of the user based on the detected activity, and suggest one or more tasks to be performed based on the inferred user location.

    Abstract translation: 用于提高家庭环境中的个人生产率的方法和系统可以存储与知识库中的环境和一个或多个用户相关联的状态信息,检测到的用户活动,基于检测到的活动推断用户的位置,并且建议一个或多个 基于推测的用户位置执行的任务。

    Optimizing Evaluation Patterns and Data Acquisition for Stream Analytics in Resource-Constrained Wireless Environments
    3.
    发明申请
    Optimizing Evaluation Patterns and Data Acquisition for Stream Analytics in Resource-Constrained Wireless Environments 有权
    优化资源约束无线环境中流分析的评估模式和数据采集

    公开(公告)号:US20140074982A1

    公开(公告)日:2014-03-13

    申请号:US14081308

    申请日:2013-11-15

    Abstract: 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.

    Abstract translation: 移动无线设备可以从多个远程传感器接收数据流。 传感器可能具有有限的电源和存储容量。 本发明的各方面使用传感器数据流的统计特征和获取每个流的单个元素的成本来确定传感器应该发送其数据流的顺序。获取数据的成本可以根据参数动态地修改 如块大小。 附加因素,如传感器的缓冲区容量,可能会限制可能被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来动态地修改评估顺序,以反映底层传感器流元组的变化的统计信息和与各个流相关联的时变获取成本。 这有助于增加传感器和相关监控应用的使用寿命。

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