基于时间效率技术的云大传感器数据错误检测

J. Pansare, V. Bajad
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引用次数: 4

摘要

传感器大数据是指工业和科研应用中产生的海量数据。云计算提供了一个特殊的平台来支持这一挑战,因为它以低成本的可伸缩方式提供了灵活的海量数据、存储和不同的软件服务。近年来,在云上处理传感器数据的技术不断发展,如传感器云。但是,这些技术并不能为大传感器数据中的错误快速检测和定位提供有效的支持。为了对大传感器数据集进行更快的错误检测,本系统开发了一种新的数据错误检测方法,充分发挥了云平台的特点和无线传感器网络(WSN)的网络特性。首先对一组传感器数据误差类型进行分类并进行定义;具体而言,在本文系统中,错误检测基于无标度网络拓扑,并且大多数检测操作可以以聚类形式进行,而不是整个大数据集。
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Errors Detection in Big Sensor Data on Cloud using Time Efficient Technique
Big sensor data is huge amount of data in both industry and scientific research application in which it generate high quantity of data. Cloud computing provides a special platform to support this challenge as it provides a flexible massive data, storage, and different software services in a scalable manner at low cost. Different technique has been developing in recent years for processing sensor data on cloud, such as sensor-cloud. But, these techniques do not provide efficient support on fast detection and locating of errors in big sensor data. For faster error detection in big sensor data sets, in this system, it develop a novel data error detection approach which gives the full feature of cloud platform and the network feature of Wireless sensor network(WSN). Firstly, it classifies a set of sensor data error types and then defined it. Specifically, in proposed system, the error detection is based on the scale-free network topology and most of detection operations can be conducted in clustered form not a whole big data set.
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