光通信技术2024，Vol.48Issue(3)：45-51,7.DOI:10.13921/j.cnki.issn1002-5561.2024.03.009
面向边缘光算力网络的上行链路资源协同调度算法
Uplink resource coordinated scheduling algorithm for edge-oriented optical computing power networks
摘要
Abstract
In order to meet the real-time and efficient computing power scheduling requirements of hot and cold services,a com-putational load prediction model(abbreviated as C-TCN model)based on adaptive noise complete set empirical mode decompo-sition(CEEMDAN)and time convolutional network(TCN)is proposed,and a resource cooperative scheduling algorithm(CTQ algorithm)based on C-TCN and Q learning is designed.The C-TCN model is used to sense the load change at the next time in advance,and the optimal wavelength partitioning and edge storage allocation scheme is found through Q learning.The experi-mental results show that the CTQ algorithm not only has better scheduling performance than the existing scheduling algorithms,but also can meet the requirements of hot and cold service scheduling performance,and improve the wavelength utilization rate.关键词
边缘光算力网络/算力调度/数据传输/资源调度/网络优化Key words
edge optical computing power network/computing power scheduling/data transfer/resource scheduling/network optimization分类
信息技术与安全科学引用本文复制引用
王蕴,林霄,楼芝兰,李军,孙卫强..面向边缘光算力网络的上行链路资源协同调度算法[J].光通信技术,2024,48(3):45-51,7.基金项目
国家自然科学基金青年项目(批准号:61901118、12001483)资助 （批准号:61901118、12001483）
上海交通大学"区域光纤通信网与新型光通信系统国家重点实验室"开放基金(批准号:2023GZKF020)资助 （批准号:2023GZKF020）
江苏省新型光纤技术与通信网络工程研究中心开放研究课题(批准号:SDGC2232)资助. （批准号:SDGC2232）
