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An interactive smart grid communication approach for big data traffic

机译:大数据流量的交互式智能电网通信方法

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As smart grid technologies begin to mature, the kinds of electrical devices have grown increasingly popular. Powerful computing capacity is required to analyze the power data fetched from electronic devices to recognize the device status for smarter applications of tomorrow. To ensure the accuracy and reliability of the analysis results, all the power data has to be uploaded to the cloud data center. This means that the cloud data center must take the extra data transmission load from the electronic devices simultaneously. The development of a lightweight communication approach for big data traffic that can prevent or quickly respond to the occurrence of network congestion presents an interesting challenge with respect to computing power and bandwidth limits. The main purpose of this study is to design an adaptive dynamic eigenvalue transmission approach that can dynamically minimize the uploaded power data through the intersection dynamic eigenvalue decision-making model, to achieve the optimal benefit between the transmission load and analysis accuracy. (C) 2018 Elsevier Ltd. All rights reserved.
机译:随着智能电网技术开始成熟,各种电气设备已经增长越来越受欢迎。需要强大的计算能力来分析从电子设备获取的电源数据,以识别明天智能应用的设备状态。为确保分析结果的准确性和可靠性,必须将所有电源数据上载到云数据中心。这意味着云数据中心必须同时从电子设备获取额外的数据传输负载。用于大数据流量的轻量级通信方法的开发,可以防止或快速响应网络拥塞的发生对计算能力和带宽限制具有令人兴趣的挑战。本研究的主要目的是设计一种自适应动态特征值传输方法,可以通过交叉动态特征值决策模型动态地减少上传的电力数据,以实现传输负载和分析精度之间的最佳益处。 (c)2018年elestvier有限公司保留所有权利。

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