Abstract
In large modern telecommunication networks, the amount of traffic and the number of nodes and links are so large that the traditional network control may not be effective due to high complexity. These networks need adaptive and intelligent systems in order to provide high network reliability, accurate traffic prediction, efficient use of channel bandwidth, and optimized network management in relation to various, dynamically changing environments. Neural networks can contribute to this emerging new telecommunication infrastructure by providing fast, flexible, adaptive, and intelligent control that cannot be performed sufficiently well by digital computers. In this paper, we discuss the neural network approaches for solving various control problems in high-speed communication networks, and present our proposed neural network model for the optimized control of input queues in ATM switches.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the IEEE Computer Society Workshop on Future Trends of Distributed Computing Systems |
| Place of Publication | Los Alamitos, CA, United States |
| Publisher | IEEE |
| Pages | 369-375 |
| Number of pages | 7 |
| Publication status | Published - 1995 Jan 1 |
| Externally published | Yes |
| Event | Proceedings of the 5th IEEE Computer Society Workshop on Future Trends of Distributed Computing Systems - Cheju Island, South Korea Duration: 1995 Aug 28 → 1995 Aug 30 |
Other
| Other | Proceedings of the 5th IEEE Computer Society Workshop on Future Trends of Distributed Computing Systems |
|---|---|
| City | Cheju Island, South Korea |
| Period | 95/8/28 → 95/8/30 |
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ASJC Scopus subject areas
- Computer Science(all)
- Engineering(all)
Cite this
Intelligent congestion control in ATM networks. / Park, Young Keun; Lee, Kyung Ho.
Proceedings of the IEEE Computer Society Workshop on Future Trends of Distributed Computing Systems. Los Alamitos, CA, United States : IEEE, 1995. p. 369-375.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Intelligent congestion control in ATM networks
AU - Park, Young Keun
AU - Lee, Kyung Ho
PY - 1995/1/1
Y1 - 1995/1/1
N2 - In large modern telecommunication networks, the amount of traffic and the number of nodes and links are so large that the traditional network control may not be effective due to high complexity. These networks need adaptive and intelligent systems in order to provide high network reliability, accurate traffic prediction, efficient use of channel bandwidth, and optimized network management in relation to various, dynamically changing environments. Neural networks can contribute to this emerging new telecommunication infrastructure by providing fast, flexible, adaptive, and intelligent control that cannot be performed sufficiently well by digital computers. In this paper, we discuss the neural network approaches for solving various control problems in high-speed communication networks, and present our proposed neural network model for the optimized control of input queues in ATM switches.
AB - In large modern telecommunication networks, the amount of traffic and the number of nodes and links are so large that the traditional network control may not be effective due to high complexity. These networks need adaptive and intelligent systems in order to provide high network reliability, accurate traffic prediction, efficient use of channel bandwidth, and optimized network management in relation to various, dynamically changing environments. Neural networks can contribute to this emerging new telecommunication infrastructure by providing fast, flexible, adaptive, and intelligent control that cannot be performed sufficiently well by digital computers. In this paper, we discuss the neural network approaches for solving various control problems in high-speed communication networks, and present our proposed neural network model for the optimized control of input queues in ATM switches.
UR - http://www.scopus.com/inward/record.url?scp=0029201869&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0029201869&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:0029201869
SP - 369
EP - 375
BT - Proceedings of the IEEE Computer Society Workshop on Future Trends of Distributed Computing Systems
PB - IEEE
CY - Los Alamitos, CA, United States
ER -