Browsing by Author "Rananand, N."
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Item Approximating a Variable Bit Rate Source by Markov Processes(1994) Rananand, N.; ISRWe consider the problem of approximating a variable bit rate (VBR) source by a simple process such that the corresponding buffer-related performance measure are close approximations of the true performance measures. Assuming that a VBR source can be modeled by a discrete-time batch Markovian arrival process (D- BMAP), we propose an approach for approximating it by a ﲭatched Markov process of finite memory obtained by information-theoretic techniques. We confirm analytically that the approximating performance measures become increasingly accurate with the memory of the matched Markov process. When the parameters of the D-BMAP are unknown, we estimate instead the parameters of a suitable Markov approximation from samples of an observed cell stream. We show that the estimated Markov process, with a fixed memory, comes closer with increasing sample size to the D-BMAP, as do the corresponding performance measures, in accordance with the law of iterated logarithm. Numerical examples are presented to illustrate the effectiveness of the approach.Item A Software Facility for the Performance Analysis of a Finite- Buffer ATM Transmission Link(1993) Rananand, N.; Pal, F.M.; ISR; CSHCNWe develop a software facility for the performance analysis of an ATM transmission link. The link is modeled by a discrete-time single server queue with a FIFO finite buffer. This software facility is capable of providing the probability of cell loss due to buffer overflow and average delay of a cell in the buffer, when fed by statistically multiplexed traffic. Such a source of traffic is modeled by a class of stochastic processes. In particular, we represent a source of multiplexed traffic by a Discrete-time Batch Markovian Arrival Process (D-BMAP). Given samples of a cell stream from an unknown source, we approximate the performance measures of the ATM link using an estimated Markov process as a source. This approach is motivated by our analytical results. We then verify the usefulness of this approach through numerical results.This work is a part of project COWS No. 5 at the Center for Satellite and Hybrid Communication Networks.