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2009 International Conference on Advanced Information Networking and Applications
ANFIS Based AQM Controller for Congestion Control
Bradford, United Kingdom
May 26-May 29
ISBN: 978-0-7695-3638-5
ASCII Text
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Rafe Alasem, Alamgir Hossain, Irfan Awan, Hussein Mansour, "ANFIS Based AQM Controller for Congestion Control," Advanced Information Networking and Applications, International Conference on, pp. 217-224, 2009 International Conference on Advanced Information Networking and Applications, 2009.
 
 
BibTex
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@article{ 10.1109/AINA.2009.125,
author = {Rafe Alasem and Alamgir Hossain and Irfan Awan and Hussein Mansour},
title = {ANFIS Based AQM Controller for Congestion Control},
journal ={Advanced Information Networking and Applications, International Conference on},
volume = {0},
year = {2009},
issn = {1550-445X},
pages = {217-224},
doi = {http://doi.ieeecomputersociety.org/10.1109/AINA.2009.125},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Advanced Information Networking and Applications, International Conference on
TI - ANFIS Based AQM Controller for Congestion Control
SN - 1550-445X
SP217
EP224
A1 - Rafe Alasem,
A1 - Alamgir Hossain,
A1 - Irfan Awan,
A1 - Hussein Mansour,
PY - 2009
KW - Congestion Control
KW - Active Queue Management
KW - Random Early Detection
KW - Neural Networks
KW - Fuzzy Logic
VL - 0
JA - Advanced Information Networking and Applications, International Conference on
ER -
 
Congestion Control is concerned with allocating the network resources such that the network can operate at an optimum performance level when the demand exceeds or it is near the capacity of the network resources. This paper presents a novel scheme of adaptive Neuro-Fuzzy Inference Controller (ANFIS). The advantages of both Fuzzy Logic and Neural Networks are combined together to design the ANFIS. A detailed comparison with the previous developed AQM controller Random Early Detection (RED) has been proposed. Finally, a simulation platform is developed, tested and validated to demonstrate the merits and capabilities of the proposed controller through a set of experiments and scenarios.
Index Terms:
Congestion Control, Active Queue Management, Random Early Detection, Neural Networks, Fuzzy Logic
Citation:
Rafe Alasem, Alamgir Hossain, Irfan Awan, Hussein Mansour, "ANFIS Based AQM Controller for Congestion Control," aina, pp.217-224, 2009 International Conference on Advanced Information Networking and Applications, 2009
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