FL4SDN: A Fast-Convergent Federated Learning for Distributed and Heterogeneous SDN

IF 5.6 3区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE IEEE Intelligent Systems Pub Date : 2024-09-04 DOI:10.1109/mis.2024.3453308
Hai-Anh Tran, Duc Tran
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FL4SDN:面向分布式和异构 SDN 的快速收敛联合学习
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来源期刊
IEEE Intelligent Systems
IEEE Intelligent Systems 工程技术-工程:电子与电气
CiteScore
13.80
自引率
3.10%
发文量
122
审稿时长
1 months
期刊介绍: IEEE Intelligent Systems serves users, managers, developers, researchers, and purchasers who are interested in intelligent systems and artificial intelligence, with particular emphasis on applications. Typically they are degreed professionals, with backgrounds in engineering, hard science, or business. The publication emphasizes current practice and experience, together with promising new ideas that are likely to be used in the near future. Sample topic areas for feature articles include knowledge-based systems, intelligent software agents, natural-language processing, technologies for knowledge management, machine learning, data mining, adaptive and intelligent robotics, knowledge-intensive processing on the Web, and social issues relevant to intelligent systems. Also encouraged are application features, covering practice at one or more companies or laboratories; full-length product stories (which require refereeing by at least three reviewers); tutorials; surveys; and case studies. Often issues are theme-based and collect articles around a contemporary topic under the auspices of a Guest Editor working with the EIC.
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