Network traffic analysis using machine learning: an unsupervised approach to understand and slice your network
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering
Link
https://link.springer.com/content/pdf/10.1007/s12243-021-00889-1.pdf
Reference33 articles.
1. Shen X, Gao J, Wu W, Lyu K, Li M, Zhuang W, Li X, Rao J (2020) Ai-assisted network-slicing based next-generation wireless networks. IEEE Open J Veh Technol 1:45–66
2. Fantacci R, Picano B (2020) When network slicing meets prospect theory: A service provider revenue maximization framework. IEEE Trans Veh Technol 69(3):3179–3189
3. Boutaba R, Salahuddin MA, Limam N, Ayoubi S, Shahriar N, Estrada-Solano F, Caicedo OM (2018) A comprehensive survey on machine learning for networking: evolution, applications and research opportunities. J Internet Serv Appl 9(1):1–99
4. Li X, Samaka M, Chan HA, Bhamare D, Gupta L, Guo C, Jain R (2017) Network slicing for 5g: Challenges and opportunities. IEEE Internet Comput 21(5):20–27
5. Abidi MH, Alkhalefah H, Moiduddin K, Alazab M, Mohammed MK, Ameen W, Gadekallu TR (2021) Optimal 5g network slicing using machine learning and deep learning concepts. Comput Stand Interfaces, p 103518
Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Enhancing 5G network slicing for IoT traffic with a novel clustering framework;Pervasive and Mobile Computing;2024-11
2. A novel graph convolutional networks model for an intelligent network traffic analysis and classification;International Journal of Information Technology;2024-08-14
3. Machine Learning in Cybersecurity: Advanced Detection and Classification Techniques for Network Traffic Environments;EAI Endorsed Transactions on Industrial Networks and Intelligent Systems;2024-07-01
4. Reliable feature selection for adversarially robust cyber-attack detection;Annals of Telecommunications;2024-06-07
5. Service-aware real-time slicing for virtualized beyond 5G networks;Computer Networks;2024-06
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3