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It has been reported that IP packet traffic exhibits the self-similar nature and causes the degradation of network performance. Therefore it is crucial for the appropriate buffer design of routers and switches to predict the queueing behavior with self-similar input. It is well known that the fitting methods based on the second-order statistics of counts for the arrival process are not sufficient for predicting the performance of the queueing system with self-similar input. However recent studies have revealed that the loss probability of finite queuing system can be well approximated by the Markovian input models. This paper studies the time-scale impact on the loss probability of *MMPP*/*D*/1/*K* system where the *MMPP* is generated so as to match the variance of the self-similar process over specified time-scales. We investigate the loss probability in terms of system size, Hurst parameters and time-scales. We also compare the loss probability of resulting *MMPP*/*D*/1/*K* with simulation. Numerical results show that the loss probability of *MMPP*/*D*/1/*K* are not significantly affected by time-scale and that the loss probability is well approximated with resulting *MMPP*/*D*/1/*K*.

- Publication
- IEICE TRANSACTIONS on Communications Vol.E84-B No.8 pp.2134-2141

- Publication Date
- 2001/08/01

- Publicized

- Online ISSN

- DOI

- Type of Manuscript
- Special Section PAPER (Special Issue on Internet Technology)

- Category
- Traffic Measurement and Analysis

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Shoji KASAHARA, "Internet Traffic Modeling: Markovian Approach to Self-Similar Traffic and Prediction of Loss Probability for Finite Queues" in IEICE TRANSACTIONS on Communications,
vol. E84-B, no. 8, pp. 2134-2141, August 2001, doi: .

Abstract: It has been reported that IP packet traffic exhibits the self-similar nature and causes the degradation of network performance. Therefore it is crucial for the appropriate buffer design of routers and switches to predict the queueing behavior with self-similar input. It is well known that the fitting methods based on the second-order statistics of counts for the arrival process are not sufficient for predicting the performance of the queueing system with self-similar input. However recent studies have revealed that the loss probability of finite queuing system can be well approximated by the Markovian input models. This paper studies the time-scale impact on the loss probability of *MMPP*/*D*/1/*K* system where the *MMPP* is generated so as to match the variance of the self-similar process over specified time-scales. We investigate the loss probability in terms of system size, Hurst parameters and time-scales. We also compare the loss probability of resulting *MMPP*/*D*/1/*K* with simulation. Numerical results show that the loss probability of *MMPP*/*D*/1/*K* are not significantly affected by time-scale and that the loss probability is well approximated with resulting *MMPP*/*D*/1/*K*.

URL: https://global.ieice.org/en_transactions/communications/10.1587/e84-b_8_2134/_p

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@ARTICLE{e84-b_8_2134,

author={Shoji KASAHARA, },

journal={IEICE TRANSACTIONS on Communications},

title={Internet Traffic Modeling: Markovian Approach to Self-Similar Traffic and Prediction of Loss Probability for Finite Queues},

year={2001},

volume={E84-B},

number={8},

pages={2134-2141},

abstract={It has been reported that IP packet traffic exhibits the self-similar nature and causes the degradation of network performance. Therefore it is crucial for the appropriate buffer design of routers and switches to predict the queueing behavior with self-similar input. It is well known that the fitting methods based on the second-order statistics of counts for the arrival process are not sufficient for predicting the performance of the queueing system with self-similar input. However recent studies have revealed that the loss probability of finite queuing system can be well approximated by the Markovian input models. This paper studies the time-scale impact on the loss probability of *MMPP*/*D*/1/*K* system where the *MMPP* is generated so as to match the variance of the self-similar process over specified time-scales. We investigate the loss probability in terms of system size, Hurst parameters and time-scales. We also compare the loss probability of resulting *MMPP*/*D*/1/*K* with simulation. Numerical results show that the loss probability of *MMPP*/*D*/1/*K* are not significantly affected by time-scale and that the loss probability is well approximated with resulting *MMPP*/*D*/1/*K*.},

keywords={},

doi={},

ISSN={},

month={August},}

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TY - JOUR

TI - Internet Traffic Modeling: Markovian Approach to Self-Similar Traffic and Prediction of Loss Probability for Finite Queues

T2 - IEICE TRANSACTIONS on Communications

SP - 2134

EP - 2141

AU - Shoji KASAHARA

PY - 2001

DO -

JO - IEICE TRANSACTIONS on Communications

SN -

VL - E84-B

IS - 8

JA - IEICE TRANSACTIONS on Communications

Y1 - August 2001

AB - It has been reported that IP packet traffic exhibits the self-similar nature and causes the degradation of network performance. Therefore it is crucial for the appropriate buffer design of routers and switches to predict the queueing behavior with self-similar input. It is well known that the fitting methods based on the second-order statistics of counts for the arrival process are not sufficient for predicting the performance of the queueing system with self-similar input. However recent studies have revealed that the loss probability of finite queuing system can be well approximated by the Markovian input models. This paper studies the time-scale impact on the loss probability of *MMPP*/*D*/1/*K* system where the *MMPP* is generated so as to match the variance of the self-similar process over specified time-scales. We investigate the loss probability in terms of system size, Hurst parameters and time-scales. We also compare the loss probability of resulting *MMPP*/*D*/1/*K* with simulation. Numerical results show that the loss probability of *MMPP*/*D*/1/*K* are not significantly affected by time-scale and that the loss probability is well approximated with resulting *MMPP*/*D*/1/*K*.

ER -