alexa Intelligent Traffic Management Service (ITMS) For High
ISSN ONLINE(2319-8753)PRINT(2347-6710)

International Journal of Innovative Research in Science, Engineering and Technology
Open Access

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Special Issue Article

Intelligent Traffic Management Service (ITMS) For High Speed Networks Using Intel Rate Control

M. Yogeshwari M.E P1 and Deepavathi, M.Tech.2
  1. Department of CSE, K.Ramakrishnan College of Technology, Trichy, Tamilnadu, India
  2. Asst. Prof., Department of CSE, K.Ramakrishnan College of Technology, Trichy, Tamilnadu, India
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As the increase in use of computing devices such as computers, tablets and smart phones there is a huge demand for the fast-growing internet traffic. Distributed traffic management frame work has been proposed, in which routers are deployed with intelligent data rate controllers to tackle the high traffic level. The traffic control protocol is unique as other traffic control protocols have to estimate network parameters which involves link latency, bottleneck bandwidth, packet loss rate, or the number of flows in order to compute the allowed source sending rate. The fuzzy-logic based controller can measure queue size directly; it neglects various potential performance issues arising due to parameter estimations as we reduce much consumption of computation and memory resource in routers. As a network parameter, the queue size can be monitored accurately and used for making proactive decision if action should be taken to regulate the source sending rate, and thus increases the resilience of the network to traffic congestion. By the fuzzy logic technique, QoS (Quality of Service) in communication is assured by good performances of our scheme such as max-min fairness, low queuing delay and good robustness to network dynamics. The conclusion is that the results and comparisons have verified the effectiveness and made a created a new benchmark that our traffic management scheme using fuzzy-logic can achieve better performance than the existing protocols that depend entirely on the estimation of network parameter.


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