Abstract
Most of the classical self-similar traffic models are asymptotic in nature. Therefore, it is crucial for an appropriate buffer design of a switch and queuing based performance evaluation. In this paper, we investigate delay and loss behavior of the switch under self-similar fixed length packet traffic by modeling it as CMMPP/D/1 and CMMPP/D/1/K, respectively, where Circulant Markov Modulated Poisson Process (CMMPP) is fitted by equating the variance of CMMPP and that of self-similar traffic. CMMPP model is already the validated one to emulate the self-similar characteristics. We compare the analytical results with the simulation ones.
Highlights
An effective traffic model has, at least, to reproduce the first and second order statistics of the original traffic trace
Characterizing the statistical behavior of traffic is crucial for proper buffer design of switch in the network traffic to provide the quality of service (QoS)
Most of the parsimonious self-similar traffic models proposed earlier are asymptotic in nature, they are less effective in the context of queuing based performance evaluation
Summary
An effective traffic model has, at least, to reproduce the first and second order statistics of the original traffic trace. Various stochastic models have been proposed to emulate the statistical nature of self-similar network traffic over certain range of time scales. Traffic models such as Fractional Brownian Motion (FBM), Fractional Auto Regressive Integrated Moving Average (FARIMA) and Chaotic maps are proposed to characterize the self-similarity. In [4,5,6,7], Markovian arrival process (MAP) is employed to model the self-similar behavior over the desired time scales These fitting models equate the second order statistics of self-similar traffic and super-. We first overview the definition of the exact second order self-similar process and summarize some characteristics of CMMPP and we make some remarks
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