Guest editorial: AI and edge computing driven technologies and applications

作     者：Jianhui Lv Yuhui Shi Hui Cheng Zhiwei Lin Lianbo Ma Jianhui Lv;Yuhui Shi;Hui Cheng;Zhiwei Lin;Lianbo Ma

作者机构：Peng Cheng LaboratoryChina Southern University of Science and TechnologyChina University of HertfordshireUK Queen's University BelfastUK Northeastern UniversityChina 

出 版 物：《Digital Communications and Networks》 (数字通信与网络（英文版）)

年 卷 期：2023年第9卷第2期

页      面：448-449页

核心收录：

学科分类：080904[工学-电磁场与微波技术] 0810[工学-信息与通信工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 080402[工学-测试计量技术及仪器] 0804[工学-仪器科学与技术] 081001[工学-通信与信息系统] 

基　　金：supported by the National Natural Science Foundation of China(Granted No.62202247) 

主　　题：network computing edge 

摘      要：*** Emerging networking paradigms,including Information-Centric Networking(ICN)[1],Software-Defined Networking(SDN)[2],Mobile Satellite Communication Networks(MSCN)[3],and Internet of Vehicles(IoV)[4],have faced some severe *** example,the dynamic network environment makes it very hard to optimize resource *** addition,these networking paradigms usually have heterogeneous features,making it difficult to schedule traffic among different kinds of *** challenges can be addressed by the adaptive learning of Artificial Intelligence(AI)[5,6]and the edge caching of edge *** can also help establish a relatively optimal routing strategy and perform congestion control by learning the dynamic network *** like AI,edge computing[7–10]can help provide fast response to users,and deploy edge servers with strong computing and storage capabilities can greatly improve the performance of 4K/8K and VR/***,despite their ability to improve network performance,there are still many *** example,the integrated architectures and frameworks need to be clearly identified,and the related protocols need to be better defined.