Smart bandwidth management using a recurrent Neuro-Evolutionary technique

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Arshad:2014:IJCNN,

• author = "R. Arshad and G. M. Khan and S. A. Mahmud",
• booktitle = "International Joint Conference on Neural Networks (IJCNN 2014)",
• title = "Smart bandwidth management using a recurrent Neuro-Evolutionary technique",
• year = "2014",
• month = jul,
• pages = "2240--2247",
• abstract = "The requirement for correct bandwidth allocation and management in a multitude of different communication mediums has generated some exceedingly tedious challenges that need to be addressed both intelligently and with innovative solutions. Current advances in high speed broadband technologies have manifold increased the amount of bandwidth required during successful multimedia streaming. The progressive growth of Neuro-Evolutionary techniques have presented themselves as worthy options to address many of the challenges faced during multimedia streaming. In this paper a Neuro-Evolutionary technique called the Recurrent Cartesian Genetic Programming Evolved Artificial Neural Network(RCGPANN) is presented for prediction of future frame sizes. The proposed technique takes into account the traffic size trend of the historically transmitted data for future frame size prediction. The predicted frame size forms the basis for estimation of the amount of bandwidth necessary for transmission of future frame. Different linear regression and probabilistic approaches are employed to estimate the allocated bandwidth, while using the predicted frame size. Our proposed intelligent traffic size prediction along with bandwidth estimation and management results in a 98percent increased efficiency.",
• keywords = "genetic algorithms, genetic programming, Cartesian Genetic Programming",
• DOI = "doi:10.1109/IJCNN.2014.6889727",
• notes = "Also known as \cite{6889727}",

}

Genetic Programming entries for Rabia Arshad Gul Muhammad Khan Sahibzada Ali Mahmud

Citations