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Simultaneous Data Management in Sensor-Based Systems using Metadata, Disaggregation and Processing

机译:使用元数据,分组和处理的基于传感器系统的同时数据管理

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High performance sensor-based systems require distributed methods that quickly release threads and allow hardware to scale as the amount of data increases. Each sensor, component, has to handle a massive amount of data, independently, at the same time it must cooperate with other sensors, components. To facilitate rapid data processing between different components and handle the dataflow simultaneously, knowledge about the components, i.e., metadata, can be incorporated. This paper presents a sensor-based system that applies metadata on internal components and utilizes disaggregation and processing as core services to handle large amount of data from various distributed sensors. By combining components with individual advantages, the system can be designed to allow a high amount of simultaneous data to be disaggregated into the respective categories, which are processed to make information accessible and stored in a database that can easily be accessed by interested parties. To evaluate the system, performance tests have been carried out using metadata on combined components, disaggregation and processing. The tests show that it is possible to build faster and more reliable sensor-based systems that are scalable, fault tolerant and high performing.
机译:基于高性能传感器的系统需要分布式方法,即快速释放线程并允许硬件按照数据量增加。每个传感器,组件必须独立地处理大量数据,同时它必须与其他传感器,组件合作。为了便于不同组件之间的快速数据处理并同时处理数据流,可以合并有关组件的知识,即元数据。本文介绍了一种基于传感器的系统,在内部组件上应用元数据,并利用分类和处理作为核心服务来处理来自各种分布式传感器的大量数据。通过将组件与各个优点组合,系统可以被设计为允许大量的同时数据分类为相应的类别,这些类别被处理为使信息可访问并存储在可以容易被有关方面访问的数据库中。为了评估系统,在组合组件上使用元数据,分解和处理进行了性能测试。测试表明,可以构建更快,更可靠的传感器系统,可扩展,容错和高性能。

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