DocumentCode :
54869
Title :
Using Fuzzy Logic Control to Provide Intelligent Traffic Management Service for High-Speed Networks
Author :
Jungang Liu ; Yang, Oliver W. W.
Author_Institution :
Sch. of Electr. Eng. & Comput. Sci., Univ. of Ottawa, Ottawa, ON, Canada
Volume :
10
Issue :
2
fYear :
2013
fDate :
Jun-13
Firstpage :
148
Lastpage :
161
Abstract :
In view of the fast-growing Internet traffic, this paper propose a distributed traffic management framework, in which routers are deployed with intelligent data rate controllers to tackle the traffic mass. Unlike other explicit traffic control protocols that have to estimate network parameters (e.g., link latency, bottleneck bandwidth, packet loss rate, or the number of flows) in order to compute the allowed source sending rate, our fuzzy-logic-based controller can measure the router queue size directly; hence it avoids various potential performance problems arising from parameter estimations while reducing much consumption of computation and memory resources in routers. As a network parameter, the queue size can be accurately monitored and used to proactively decide if action should be taken to regulate the source sending rate, thus increasing the resilience of the network to traffic congestion. The communication QoS (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 achieve better performances than the existing protocols that rely on the estimation of network parameters.
Keywords :
Internet; fuzzy control; intelligent control; parameter estimation; quality of service; telecommunication congestion control; telecommunication network routing; telecommunication traffic; Internet traffic; communication QoS; distributed traffic management framework; fuzzy-logic-based controller; high-speed network; intelligent data rate controllers; intelligent traffic management service; parameter estimations; quality of service; router queue size; source sending rate; traffic congestion; traffic mass; Distributed processing; Fuzzy logic; Internet; Quality of service; Routing protocols; Telecommunication network management; Telecommunication traffic; Congestion control; fuzzy logic control; max-min fairness; quality of service; robustness; traffic management;
fLanguage :
English
Journal_Title :
Network and Service Management, IEEE Transactions on
Publisher :
ieee
ISSN :
1932-4537
Type :
jour
DOI :
10.1109/TNSM.2013.043013.120264
Filename :
6514996
Link To Document :
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