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This study aims to improve the accuracy of predicting first hitting times in network congestion events by developing robust estimators for long-range parameters in Internet traffic, particularly utilizing the fractional Brownian motion model. We evaluate the validity of the Hurst parameter (H) in describing the burstiness of Internet traffic and examine the potential of using the rate of congestion events as a new quality of service (QoS) metric for multimedia packet networks. Extensive simulations have been conducted to assess the performance of the proposed analytical model.
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Simulation Results Future Work • To improve the accuracy of the method for approximating the first hitting time • Develop robust estimators for the long range parameters of the Internet traffic • Determine whether the Hurst parameter, H, is valid in describing the Internet traffic burstiness Electrical Engineering and Computer Science Quantifying Temporal Characteristics of Network Congestion Events for Multimedia Services in the Internet Fractional Brownian Model & First Hitting Time Objectives • Determine the suitability of using the rate of congestion events as a new QoS metric for the multimedia packet networks. • Traffic model: fractional Brownian motion, a mathematical model, is used to capture long range dependence (LRD) in Internet traffic. : mean input rate (b/s) : service rate (b/s) : variance (bit*bit) : standard fBM with parameter H. The input traffic to the queue is assumed to be fractional Brownian motion. Premise: First hitting times can be used to predict intercongestion event times. Extensive simulations are conducted to evaluate the accuracy of the predictions obtained from the developed analytical model 042004
