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Titlebook: Networked Systems; 11th International C David Mohaisen,Thomas Wies Conference proceedings 2023 The Editor(s) (if applicable) and The Author

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發(fā)表于 2025-3-21 16:28:25 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Networked Systems
副標(biāo)題11th International C
編輯David Mohaisen,Thomas Wies
視頻videohttp://file.papertrans.cn/663/662952/662952.mp4
叢書(shū)名稱(chēng)Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Networked Systems; 11th International C David Mohaisen,Thomas Wies Conference proceedings 2023 The Editor(s) (if applicable) and The Author
描述.This book constitutes the refereed proceedings of the 11th International Conference on Networked Systems, NETYS 2023, held in?Benguerir, Morocco, during May 22–24, 2023...The 9 full papers and 3 short papers presented were carefully reviewed and selected from 31 submissions. .The scope of the conference covers all aspects related to the design and the development of these systems, including, e.g., cloud systems, formal verification, concurrent and distributed algorithms, data management, data science, parallel/concurrent/distributed programming, machine learning, multi-core architectures, networks, and security..
出版日期Conference proceedings 2023
關(guān)鍵詞Computer Science; Informatics; Conference Proceedings; Research; Applications
版次1
doihttps://doi.org/10.1007/978-3-031-37765-5
isbn_softcover978-3-031-37764-8
isbn_ebook978-3-031-37765-5Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

書(shū)目名稱(chēng)Networked Systems影響因子(影響力)




書(shū)目名稱(chēng)Networked Systems影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Networked Systems網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Networked Systems網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Networked Systems被引頻次




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書(shū)目名稱(chēng)Networked Systems年度引用




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書(shū)目名稱(chēng)Networked Systems讀者反饋




書(shū)目名稱(chēng)Networked Systems讀者反饋學(xué)科排名




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Case Study on?the?Performance of?ML-Based Network Intrusion Detection Systems in?SDNring, and model architecture. In this article, we conducted a comparative study of several ML models on the InSDN dataset. The results showed that the DT model performs well with only 7 out of the 83 features in the InSDN dataset, reducing the training time from 10 to 0.5?s.
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A Formal Analysis of?Karn’s Algorithmnt a formal description of the algorithm, and study its properties. We prove the computed samples reflect the RTT of some packets, but it is not always possible to determine which. We then study some of the properties of RTO computations as described in the commonly used RFC6298. All properties are mechanically verified.
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Conference proceedings 2023rence covers all aspects related to the design and the development of these systems, including, e.g., cloud systems, formal verification, concurrent and distributed algorithms, data management, data science, parallel/concurrent/distributed programming, machine learning, multi-core architectures, networks, and security..
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