Dengjun Zhu, Jinlong Yan, Haiwei Yuan, Yongjun Ma, Xufeng Hu
{"title":"基于DCS-PCA的智能电网数据传输","authors":"Dengjun Zhu, Jinlong Yan, Haiwei Yuan, Yongjun Ma, Xufeng Hu","doi":"10.1109/ICAIIC.2019.8669060","DOIUrl":null,"url":null,"abstract":"The safety of high speed sensor data transmission is an important part of smart grid. Due to the development of the diversity and scale, there has been an ever-increasing need of data transmission algorithms in both academia and industry. Past research shows that with the increasing types and number of sensors deployed, there are problems such as low transmission efficiency and excessive energy consumption. When the collected data are transferred back to the background server, sensor nodes face the problem of high storage pressure. Distributed technology can alleviate the transmission and storage pressure of signal nodes. Therefore, this paper proposes an optimization algorithm which can reduce the amount of data, energy consumption and improve transmission rate. In addition, for further improving the accuracy of restored data, principal component analysis (PCA) is utilized to generate adaptive sparse matrix for different types of sensors. Through selecting different sparse matrices, our experiments show that the technology can significantly reduce the transmission of data and ensure the accuracy of data reconstruction.","PeriodicalId":273383,"journal":{"name":"2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"DCS-PCA based Data Transmission in Smart Grid\",\"authors\":\"Dengjun Zhu, Jinlong Yan, Haiwei Yuan, Yongjun Ma, Xufeng Hu\",\"doi\":\"10.1109/ICAIIC.2019.8669060\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The safety of high speed sensor data transmission is an important part of smart grid. Due to the development of the diversity and scale, there has been an ever-increasing need of data transmission algorithms in both academia and industry. Past research shows that with the increasing types and number of sensors deployed, there are problems such as low transmission efficiency and excessive energy consumption. When the collected data are transferred back to the background server, sensor nodes face the problem of high storage pressure. Distributed technology can alleviate the transmission and storage pressure of signal nodes. Therefore, this paper proposes an optimization algorithm which can reduce the amount of data, energy consumption and improve transmission rate. In addition, for further improving the accuracy of restored data, principal component analysis (PCA) is utilized to generate adaptive sparse matrix for different types of sensors. Through selecting different sparse matrices, our experiments show that the technology can significantly reduce the transmission of data and ensure the accuracy of data reconstruction.\",\"PeriodicalId\":273383,\"journal\":{\"name\":\"2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAIIC.2019.8669060\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAIIC.2019.8669060","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The safety of high speed sensor data transmission is an important part of smart grid. Due to the development of the diversity and scale, there has been an ever-increasing need of data transmission algorithms in both academia and industry. Past research shows that with the increasing types and number of sensors deployed, there are problems such as low transmission efficiency and excessive energy consumption. When the collected data are transferred back to the background server, sensor nodes face the problem of high storage pressure. Distributed technology can alleviate the transmission and storage pressure of signal nodes. Therefore, this paper proposes an optimization algorithm which can reduce the amount of data, energy consumption and improve transmission rate. In addition, for further improving the accuracy of restored data, principal component analysis (PCA) is utilized to generate adaptive sparse matrix for different types of sensors. Through selecting different sparse matrices, our experiments show that the technology can significantly reduce the transmission of data and ensure the accuracy of data reconstruction.