Name
Abstract | ||
|---|---|---|
The recently proposed neural network rate control (NNRC) framework that achieves queueing delay and queue length regulation, is expanded to further guarantee fair allocation of network resources among competing sources. This is possible by introducing a novel algorithm that controls in a stable and adaptive manner the number of communication channels in each source. Simulation studies performed on a heterogeneous delay, long-distance high-speed network, illustrate all aspects of the developed methodology. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/TNN.2009.2013463 | IEEE transactions on neural networks / a publication of the IEEE Neural Networks Council |
Keywords | Field | DocType |
packet switching,congestion control,neurocontrollers,fair network resources allocation,fairness,telecommunication congestion control,queueing delay,queueing theory,delay regulation,resource allocation,neural network adaptive congestion control framework,internet,neural adaptive control,adaptive control,queue length regulation,neural network rate control framework,packet-switching networks | Telecommunications network,Computer science,Adaptive system,Queue,Computer network,Queueing theory,Resource allocation,Network congestion,Adaptive control,Packet switching | Journal |
Volume | Issue | ISSN |
20 | 3 | 1941-0093 |
Citations | PageRank | References |
2 | 0.37 | 18 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Christos N. Houmkozlis | 1 | 5 | 1.09 |
| George A. Rovithakis | 2 | 581 | 52.21 |