Zobrazeno 1 - 10
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pro vyhledávání: '"INTERNET traffic"'
Autor:
Zhang, Zhiyuan1 (AUTHOR), Ling, Chen1 (AUTHOR), He, Hongjin2 (AUTHOR), Qi, Liqun1 (AUTHOR) liqun.qi@polyu.edu.hk
Publikováno v:
Annals of Operations Research. Aug2024, Vol. 339 Issue 3, p1461-1479. 19p.
In this paper, we present a novel hybrid deep learning model, named ConvLSTMTransNet, designed for time series prediction, with a specific application to internet traffic telemetry. This model integrates the strengths of Convolutional Neural Networks
Externí odkaz:
http://arxiv.org/abs/2409.13179
Effective internet traffic prediction in smaller ISP networks is challenged by limited data availability. This paper explores this issue using transfer learning and data augmentation techniques with two LSTM-based models, LSTMSeq2Seq and LSTMSeq2SeqA
Externí odkaz:
http://arxiv.org/abs/2409.13181
The increasing popularity of online services has made Internet Traffic Classification a critical field of study. However, the rapid development of internet protocols and encryption limits usable data availability. This paper addresses the challenges
Externí odkaz:
http://arxiv.org/abs/2407.16539
Autor:
Kepner, Jeremy, Jananthan, Hayden, Jones, Michael, Arcand, William, Bestor, David, Bergeron, William, Burrill, Daniel, Buluc, Aydin, Byun, Chansup, Davis, Timothy, Gadepally, Vijay, Grant, Daniel, Houle, Michael, Hubbell, Matthew, Luszczek, Piotr, Milechin, Lauren, Milner, Chasen, Morales, Guillermo, Morris, Andrew, Mullen, Julie, Patel, Ritesh, Pentland, Alex, Pisharody, Sandeep, Prout, Andrew, Reuther, Albert, Rosa, Antonio, Wachman, Gabriel, Yee, Charles, Michaleas, Peter
Understanding what is normal is a key aspect of protecting a domain. Other domains invest heavily in observational science to develop models of normal behavior to better detect anomalies. Recent advances in high performance graph libraries, such as t
Externí odkaz:
http://arxiv.org/abs/2409.03111
Autor:
Wei, Dawei1 (AUTHOR), Shi, Feifei1 (AUTHOR), Dhelim, Sahraoui2 (AUTHOR) sahraoui.dhelim@hotmail.com
Publikováno v:
Future Internet. Oct2022, Vol. 14 Issue 5, pN.PAG-N.PAG. 16p.
Autor:
MA Yunying, WANG Shenghuan
Publikováno v:
Dianxin kexue, Vol 40, Pp 144-153 (2024)
With the development of China’s digital economy, Internet traffic has shown a steady growth trend. In view of the problem that the uneven distribution of Internet traffic will affect the long-term stable development of the network, the methods of I
Externí odkaz:
https://doaj.org/article/22737a2df7fe48b6b08649e516fe6c33
Autor:
Spitsina, Lubov1 spicyna@tpu.ru, Kretinin, Andrey2 kretinina@wpunj.edu, Spitsin, Vladislav3 spicynvv@tpu.ru
Publikováno v:
Retos, Revista de Ciencias Administrativas y Económicas. abr-sep2022, Vol. 12 Issue 23, p95-109. 15p.
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