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 |
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Pages | 369-375 |
Number of pages | 7 |
Publication status | Published - 1995 |
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 |
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City | Cheju Island, South Korea |
Period | 95/8/28 → 95/8/30 |
ASJC Scopus subject areas
- Computer Science(all)
- Engineering(all)