Your Search Results

Use this resource - and many more! - in your textbook!

AcademicPub holds over eight million pieces of educational content for you to mix-and-match your way.

Experience the freedom of customizing your course pack with AcademicPub!
Not an educator but still interested in using this content? No problem! Visit our provider's page to contact the publisher and get permission directly.

A new traffic model and statistical admission control algorithm for providing QoS guarantees to on-line traffic

By: Dauchy, P.; Yiyan Tang; Yuke Wang; Krishnamurthy, A.; Lie Qian; Conte, A.;

2004 / IEEE / 0-7803-8794-5

Description

This item was taken from the IEEE Conference ' A new traffic model and statistical admission control algorithm for providing QoS guarantees to on-line traffic ' On-line traffic, including conversational calls, videoconference calls, and live video, is becoming an important type of traffic in the Internet. The traffic traces of on-line traffic are not pre-recorded, which means little information on the on-line traffic is known in advance. Hence, on-line traffic is hard to characterize by existing traffic models, such as D-BIND. In order to anticipate and capture the burstiness property of on-line traffic, we introduce a new confidence-level-based statistical bounding interval-length dependent (S-BIND) traffic model and a statistical admission control algorithm, based on the S-BIND traffic model: the GammaH-BIND algorithm. Our simulation results show that by using the S-BIND traffic model as inputs, the GammaH-BIND algorithm can achieve the maximum valid network utilization for both low-bursty and high-bursty on-line traffic, which is 50%/spl sim/70% higher than the achievable network utilization under the D-BIND traffic model.