DocumentCode
2194996
Title
Neuron-based connection acceptance strategy
Author
Chen, Jian-Liang ; Tsai, Che-Hsien ; Jeng, Sheng-Ching ; Choy, Michael
Author_Institution
Comput. & Commun. Res. Labs., Ind. Technol. Res. Inst., Hsinchu, Taiwan
fYear
1995
fDate
20-22 Jun 1995
Firstpage
89
Lastpage
94
Abstract
A neural system with the back propagation learning algorithm is discussed for making decisions in connection management. The strategy is divided into two developed stages. In the learning stage, we collect three groups of information including the traffic description, QoS requirement, and link status, and then embed them in the input pool. The accept/reject decision for a requested service is generated in the output layer. Upon completing the learning stage, the on-line test is in progress. From the results, we found that the strategy can support the real-time feature in connection management. In addition, the QoS is guaranteed while the connection is permitted under our ATM testbed
Keywords
asynchronous transfer mode; backpropagation; multimedia communication; neural nets; real-time systems; telecommunication computing; telecommunication congestion control; telecommunication network management; ATM testbed; QoS requirement; back propagation learning algorithm; call admission control; connection management; input pool; learning stage; link status; neural system; neuron-based connection acceptance strategy; on-line test; real-time feature; requested service; traffic description; Asynchronous transfer mode; B-ISDN; Communication system traffic control; Monitoring; Neural networks; Project management; Quality management; Quality of service; Telecommunication traffic; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Community Networking, 1995. Integrated Multimedia Services to the Home., Proceedings of the Second International Workshop on
Conference_Location
Princeton, NJ
Print_ISBN
0-7803-2756-X
Type
conf
DOI
10.1109/CN.1995.509557
Filename
509557
Link To Document