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Dynamic Resource Management Considering the Real Behavior of Aggregate Traffic. Jos é R. Gallardo, Dimitrios Makrakis, and Marlenne Angulo IEEE Transaction on Multimedia, VOL. 3, NO. 2, June 2001. Outline. Motivation and Goal Dynamic traffic control using predictive techniques
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Dynamic Resource Management Considering the Real Behavior of Aggregate Traffic José R. Gallardo, Dimitrios Makrakis, and Marlenne Angulo IEEE Transaction on Multimedia, VOL. 3, NO. 2, June 2001 Chin-Kai Wu, CS, NTHU
Outline • Motivation and Goal • Dynamic traffic control using predictive techniques • Differentiated Service • Model • Traffic policing and resource allocation algorithms • Simulation Parameters and Results Chin-Kai Wu, CS, NTHU
Motivation and Goal • Theory of effective bandwidth • The probability of buffer overflow in a stationary queueing system decreases exponentially with the buffer size as long as the “effective bandwidth” of the input traffic stream is smaller than the server capacity • Goal • Propose an alternative dynamic approach to resource allocation and management Chin-Kai Wu, CS, NTHU
Differentiated Service Chin-Kai Wu, CS, NTHU
Model marker Chin-Kai Wu, CS, NTHU
Traffic policing • Two different policing mechanisms that are based on the leaky bucket idea: conventional leaky bucketand adaptive leaky bucket assisted by traffic prediction. • The purpose is to optimize the resource utilization, which in turn intends to minimize the number of violations to the QoS requirements of the traffic. Chin-Kai Wu, CS, NTHU
Packets arrive Generate token each constant time NO YES Buffer full YES Pool full Got Token NO NO YES Drop Put Drop Send Wait Conventional Leaky Bucket (CLB) Chin-Kai Wu, CS, NTHU
Adaptive Leaky Bucket Assisted by Traffic Prediction (PALB) Buffer occupancy above upper bond YES NO Buffer occupancy below lower bond Increase generation rate NO YES Maintain generation rate Decrease generation rate Chin-Kai Wu, CS, NTHU
Simulation Parameters Chin-Kai Wu, CS, NTHU
Results Chin-Kai Wu, CS, NTHU