Call for Paper - August 2019 Edition
IJCA solicits original research papers for the August 2019 Edition. Last date of manuscript submission is July 20, 2019. Read More

Traffic and Congestion Control in ATM Networks Using Neuro-Fuzzy Approach

Print
PDF
IJCA Special Issue on Communication Security
© 2012 by IJCA Journal
comnetcs - Number 1
Year of Publication: 2012
Authors:
Suriti Gupta
Vinod Kumar

Suriti Gupta and Vinod Kumar. Article: Traffic and Congestion Control in ATM Networks Using Neuro-Fuzzy Approach. IJCA Special Issue on Communication Security comnetcs(1):45-49, March 2012. Full text available. BibTeX

@article{key:article,
	author = {Suriti Gupta and Vinod Kumar},
	title = {Article: Traffic and Congestion Control in ATM Networks Using Neuro-Fuzzy Approach},
	journal = {IJCA Special Issue on Communication Security},
	year = {2012},
	volume = {comnetcs},
	number = {1},
	pages = {45-49},
	month = {March},
	note = {Full text available}
}

Abstract

In this paper, a neuro-fuzzy based Call Admission Control (CAC) algorithm for ATM networks has been simulated. The algorithm presented employs neuro-fuzzy approach to calculate the bandwidth require to support multimedia traffic with QoS requirements. The neuro-fuzzy based CAC calculates bandwidth required per call using measurements of the traffic via its count-process, instead of relying on simple parameters such as the peak, average bit rate and burst length. Furthermore, to enhance the statistical multiplexing gain, the controller calculates the gain obtained from multiplexing multiple streams of traffic supported on separate virtual (i.e, class multiplexing).

References

  • F. Bonomi and K. Fendick, “The ratebased flow control framework for the ABR ATM service,” IEEE Network, vo1.9, n0.2, pp. 25-39, 1995.
  • F. Bonomi and K. Fendick, "The rate-based flow control framework for the ABR ATM service," IEEE Nerwork, vo1.9,no.2, pp. 25-39,1995.
  • B. Chen, Y. Zhang, J. Yen, and W. Zhao, "Fuzzy adaptive connection admission control for real-time applications in ATM-based heterogeneous networks," Jotirnal of Intelligent and Fmq~ Systems, vo1.7, no.2, 1999.
  • R.-G. Cheng, C.-J. Chang, and L.-F. Lin, "A QoS provisioning neural fuzzy connection admission controller for multimedia high-speed networks," IEEG'ACM Transaction on Networking, ~01.7, no.1, pp. 1 1 1-121, 1999.
  • A. Hiramatsu, "ATM communications network control by neural networks," IEEE Transaction on netiraf networks, vol.l,no.l,pp.122-130, 1990.
  • T.V.Lakshman, P. P. Mishra and K.K. Ramakrishnan, "Transporting compressed video over ATM networks with explicit-rate feedback control," IEEE/ACM Transactions on Networking, Vol. 7,No. 5, October 1999.
  • Parag Jain, Sandip Vijay and S. C. Gupta “Fuzzy Congestion Control Scheme in ATM Networks”. Global Journal of Computer Science and Technology, Vol. 9 Issue 5 (Ver. 2.0), January 2010 PP 68.