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A Novel Big Data Cleaning Algorithm Based On Edge Computing In Industrial Internet of Things

机译:一种基于边缘计算的工业物联网大数据清洗算法

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The Industrial Internet of Things(IIoT) is a revolution that is changing the face of industry. It brings opportunities and also challenges. Due to the harsh sensor environment in the industry, the collected big data is not credible, which seriously affects the judgment and feedback of the cloud. Traditional data cleaning relying on sensor nodes is not enough to process big data, while mobile edge computing can provide a good solution. The paper proposes a data cleaning solution based on mobile edge nodes. First,we obtain the training data of the cleaning model. Second, we use the isolation forest (iForest) anomaly detection method at the edge nodes. Experimental results show that the scheme improves the efficiency of data cleaning and also ensures the reliability and integrity of the data.
机译:工业物联网(IIoT)是一场正在改变工业面貌的革命。它既带来机遇,也带来挑战。由于行业传感器环境恶劣,采集到的大数据不可信,严重影响云的判断和反馈。传统的依靠传感器节点的数据清洗不足以处理大数据,而移动边缘计算可以提供一个很好的解决方案。提出了一种基于移动边缘节点的数据清洗方案。首先,获取清洗模型的训练数据。其次,我们在边缘节点使用隔离林(iForest)异常检测方法。实验结果表明,该方案提高了数据清洗的效率,保证了数据的可靠性和完整性。

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