Design of QoS in Intelligent Communication Environments Based on Neural Network |
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Authors: | N Xiong L T Yang Y Yang J H Park G Wei |
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Affiliation: | (1) State University of New York Binghamton, Binghamton, NY 13902, USA |
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Abstract: | Due to the latest developments in communication and computing, smart services and applications are being deployed for various
applications such as entertainment, health care, smart homes, security and surveillance. In intelligent communication environments,
the main difficulty arising in designing an efficient congestion control scheme lies in the large propagation delay in data
transfer which usually leads to a mismatch between the network resources and the amount of admitted traffic. To attack this
problem, this paper describes a novel congestion control scheme in intelligent communication environments, which is based
on a Back Propagation (BP) neural network technique. We consider a general computer communication model with multiple sources
and one destination node. The dynamic buffer occupancy of the bottleneck node is predicted and controlled by using a BP neural
network. The controlled best-effort traffic of the sources uses the bandwidth, which is left over by the guaranteed traffic.
This control mechanism is shown to be able to avoid network congestion efficiently and to optimize the transfer performance
both by the theoretic analyzing procedures and by the simulation studies. |
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Keywords: | |
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