• Journal of Communications and Networks
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• v.17 no.5
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• pp.534-540
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• 2015

In this paper we propose an analytical model for jitter, wherein we implement the interrupted Poisson process (IPP) for incoming traffic. First, we obtain an analytical model for the jitter on one node with respect to the phase probabilities, traffic load, and tagged traffic share in the aggregate traffic flow. Then, we analyze N-node cases, and propose a model for end-to-end jitter. Our analysis leads to some fast-to-compute approximations that can be used for future network design or admission control. Finally, we validate our analytical results by comparing them with previous results for limit cases, as well as with event-driven simulations. We propose the use of our results as guidelines for jitter evaluation of real IP traffic.

• Journal of KIISE:Information Networking
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• v.30 no.3
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• pp.416-423
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• 2003

This paper proposes a continuous-time queuing model of a shared-buffer packet switch and an approximate algorithm. N arrival processes have heterogeneous busty traffic characteristics. The arrival processes are modeled by Coxian distribution with order 2 that is equivalent to Interruped Poisson Process. The service time is modeled by Erlang distribution with r stages. First the approximate algorithm performs the aggregation of N arrival processes as a single state variable. Next the algorithm discompose the queuing system into N subsystems which are represented by aggregated state variables. And the balance equations based on these aggregated state variables are solved for by iterative method. Finally the algorithm is validated by comparing the results with those of simulation.

• Journal of applied mathematics & informatics
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• v.30 no.1_2
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• pp.135-145
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• 2012

Traditionally, ERM (Equivalent Random Method) is used to determine number of circuits in an overflow circuit group with rough traffic which has vmr(variance to mean ratio) greater than one. Recently, IPP(Interrupted Poisson Process) approximate method which represents the collective feature of the overflow has been introduced. The negative binomial loss formula can be applied to determine the required number of circuits in the overflow circuit group. In this paper, we deal with the negative binomial loss formula and determination method of number of circuits. We also analyze and compare these three loss formulas.