Naive-LSTM enabled service identification of edge computing in power Internet of things  

作　　者：Bai Huifeng Huo Chao Zhang Ganghong Yin Zhibin 

机构地区：[1]Beijing Smart-Chip Microelectronics Technology Company Limited,Beijing 102200,China

出　　处：《The Journal of China Universities of Posts and Telecommunications》2024年第5期34-41,共8页中国邮电高校学报（英文版）

基　　金：supported by the National Key Research and Development Program of China(2021YFB2401304)。

摘　　要：Great challenges and demands are presented by increasing edge computing services for current power Internet of things(Power IoT)to deal with the serious diversity and complexity of these services.To improve the matching degree between edge computing and complex services,the service identification function is necessary for Power IoT.In this paper,a naive long short-term memory(Naive-LSTM)based service identification scheme of edge computing devices in the Power IoT was proposed,where the Naive-LSTM model makes full use of the most simplified structure and conducts discretization of the long short-term memory(LSTM)model.Moreover,the Naive-LSTM based service identification scheme can generate the probability output result to determine the task schedule policy of Power IoT.After well learning operation,these Naive-LSTM classification engine modules in edge computing devices of Power IoT can perform service identification,by obtaining key characteristics from various service traffics.Testing results show that the Naive-LSTM based services identification scheme is feasible and efficient in improving the edge computing ability of the Power IoT.

关 键 词：power Internet of things(Power IoT) naive long short-term memory(Naive-LSTM) services identification edge computing 

分 类 号：TM73[电气工程—电力系统及自动化] TN929.5[电子电信—通信与信息系统] TP393[电子电信—信息与通信工程]