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A self-managed architecture for sensor networks based on real time data analysis

机译:基于实时数据分析的传感器网络自我管理架构

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Wireless sensor networks (WSNs) have been adopted as merely data producers for years. However, the data collected by WSNs can also be used to manage their operation and avoid unnecessary measurements that do not provide any new knowledge about the environment. The benefits are twofold because wireless sensor nodes may save their limited energy resources and also reduce the wireless medium occupancy. We present a self-managed platform that collects and stores data from sensor nodes, analyzes its contents and uses the built knowledge to adjust the operation of the entire network. The system architecture facilitates the incorporation of traditional WSNs into the Internet of Things by abstracting the lower communication layers and allowing decisions based on the data relevance. Finally, we demonstrate the platform optimizing a WSN's operation at runtime, based on different real-time data analysis.
机译:多年来,无线传感器网络(WSN)仅被用作数据生产者。但是,由WSN收集的数据也可以用于管理其操作,并避免不必要的测量,这些测量不会提供有关环境的任何新知识。好处是双重的,因为无线传感器节点可以节省其有限的能源,还可以减少无线介质的占用。我们提供了一个自我管理的平台,该平台从传感器节点收集和存储数据,分析其内容,并使用已建立的知识来调整整个网络的运行。该系统体系结构通过抽象化较低的通信层并允许基于数据相关性的决策来促进将传统WSN整合到物联网中。最后,我们演示了基于不同的实时数据分析在运行时优化WSN操作的平台。

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