Smart Traffic Management in High-Speed Networks by Fuzzy Logic Control

Kadanti Theja, P. Lakshmi Samyuktha

Abstract In view of the fast-emerging Internet traffic, this paper propose a distributed traffic management framework, in which routers are installed with intelligent data rate controllers to handle the traffic mass. Unlike other explicit traffic control protocols that have to evaluate network parameters in order to calculate the allowed source sending rate, our fuzzy-logic-based controller can calculate the router queue size directly; hence it avoids various potential performance problems arising from parameter estimations while decreasing much consumption of computation and memory resources in routers. As a network parameter, the queue size can be accurately observed and used to proactively decide if action should be taken to control the source sending rate, thus increasing the resilience of the network to traffic congestion. The communication Quality of Service is assured by the good performances of our scheme such as max-min fairness, low queueing delay and good robustness to network dynamics. Simulation results and comparisons have verified the effectiveness and showed that our new traffic management scheme can attain better performances than the existing protocols that depend on the estimation of network parameters. Key words: Congestion control, fuzzy logic control, quality of service, max-min fairness, robustness, traffic management

Title:	Smart Traffic Management in High-Speed Networks by Fuzzy Logic Control
Author Name:	Kadanti Theja, P. Lakshmi Samyuktha
Abstract:	Abstract In view of the fast-emerging Internet traffic, this paper propose a distributed traffic management framework, in which routers are installed with intelligent data rate controllers to handle the traffic mass. Unlike other explicit traffic control protocols that have to evaluate network parameters in order to calculate the allowed source sending rate, our fuzzy-logic-based controller can calculate the router queue size directly; hence it avoids various potential performance problems arising from parameter estimations while decreasing much consumption of computation and memory resources in routers. As a network parameter, the queue size can be accurately observed and used to proactively decide if action should be taken to control the source sending rate, thus increasing the resilience of the network to traffic congestion. The communication Quality of Service is assured by the good performances of our scheme such as max-min fairness, low queueing delay and good robustness to network dynamics. Simulation results and comparisons have verified the effectiveness and showed that our new traffic management scheme can attain better performances than the existing protocols that depend on the estimation of network parameters. Key words: Congestion control, fuzzy logic control, quality of service, max-min fairness, robustness, traffic management
Cite this article:	Kadanti Theja, P. Lakshmi Samyuktha , " Smart Traffic Management in High-Speed Networks by Fuzzy Logic Control " , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS), Volume 3, Issue 4, July - August 2014 , pp. 262-268 , ISSN 2278-6856.
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