Naive-LSTM based services awareness of edge computing elastic optical networks

作     者：HUO Chao BAI Huifeng YIN Zhibin YAN Bo HUO Chao;BAI Huifeng;YIN Zhibin;YAN Bo

作者机构：Beijing SmartChip Microelectronics Technology Company LimitedBeijing 102200China Huakeyinnuo(Tianjin)Energy Technology Co.Ltd.Tianjin 300143China 

出 版 物：《Optoelectronics Letters》 (光电子快报（英文版）)

年 卷 期：2023年第19卷第5期

页      面：279-283页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 081104[工学-模式识别与智能系统] 0835[工学-软件工程] 0803[工学-光学工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the National Key Research and Development Program of China(No.2021YFB2401304) 

主　　题：optical services LSTM 

摘      要：Great challenges and demands are presented by increasing edge computing services for current elastic optical networks(EONs)to deal with serious diversity and complexity of these *** improve the match degree between edge computing and optical network,the services awareness function is necessary for *** article proposes a Naive long short-term memory(Naive-LSTM)based services awareness strategy of the EON,where the Naive-LSTM model makes full use of the most simplified structure and conducts discretization of the LSTM ***,the proposed algorithm can generate the probability output result to determine the quality of service(Qo S)policy of *** well learning operation,these Naive-LSTM classification agents in edge nodes of EONs are able to perform services awareness by obtaining data traffic characteristics from services *** results show that the proposed approach is feasible and efficient to improve edge computing ability of EONs.