Abstract
We developed the Remote Monitoring Intelligent System (RMIS) of Local Area Network (LAN) to realize the secure Internet environment. The RMIS has various agents which work to exchange the information related to computers condition with the network environment. We shall be able to control the quality and quantity in the network communication by their agents. In this paper, we propose the scheduling method of data transmission by Recurrent Neural Networks(RNNs) to avoid traffic jam in the network. Especially, our proposed RNN enables to expect the condition of network at each network device instead of time series data. In order to verify the effectiveness of our proposed method, we report the examination results.
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References
CERT Coordination Center(2005), http://www.cert.org/
Williams, R., Zipser, D.: A learning algorithm for continually running fully recurrent neural networks. Neural Computation 1, 270–280 (1989)
Williams, R., Zipser, D.: Gradient-based learning algorithms for recurrent networks and their computational complexxity. In: Chauvin, Y., Rumelhart, D.E. (eds.) Backpropagation: Theory, Architectures, and Applications, pp. 433–484. Lawrence Erlbaum Associate, Publishers, New Jersey (1995)
Robertson, R.: Examine Your Network with Ping and Traceroute(1997), http://webmonkey.wired.com/webmonkey/geektalk/97/42/index3a.html
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© 2005 Springer-Verlag Berlin Heidelberg
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Ozaki, N., Ichimura, T. (2005). A Scheduling Method of Data Transmission in the Internet Communication by Recurrent Neural Network. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3683. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11553939_174
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DOI: https://doi.org/10.1007/11553939_174
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28896-1
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