摘要

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.

  • 出版日期2018-4