Dependence in packet queues

Fendick, Kerry W.; Saksena, V.R.; Whitt, Ward

doi:10.1109/26.46511

Cited by 120 publications

(45 citation statements)

References 32 publications

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“…-autocorrelations in packet interarrival times -autocorrelations in packet service times -crosscorrelations among packet interarrival times and packet service times -crosscorrelations in packet service times for tandem queues Generally, successive packet interarrival times are often positively correlated [11]. This is valid for successive packet service times as well.…”

Section: Queueing Delay In Chained Ip Routersmentioning

confidence: 78%

“…On the other hand, under heavy loads, the average delay tends to be dramatically less. A reverse situation is valid under light traffic conditions as well [11].…”

Section: Queueing Delay In Chained Ip Routersmentioning

confidence: 99%

“…On the other hand, packet interarrival times and packet service times are often negatively correlated with each other. Altogether, the above-mentioned types of correlations tend to make packet delays larger than in the case of independent and identically distributed (iid) packet lengths where there is no dependence [11].…”

Section: Queueing Delay In Chained Ip Routersmentioning

confidence: 99%

“…There are several classes of correlations in a queueing system, all of them contributing to the complexity of the process of changing the character of the arrival process at downstream queues [11]. These are:…”

Section: Queueing Delay In Chained Ip Routersmentioning

confidence: 99%

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On Kleinrock’s Independence Assumption

Popescu

Constantinescu²

2011

Network Performance Engineering

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Abstract. This chapter is concerned with the impact of traffic correlations on the end-to-end delay of packets in a chain of IP routers represented by an open tandem queueing system. Particular consideration is given to Kleinrock's independence assumption on the performance impact of traffic correlation on packet switched networks with Poisson arrival processes and exponential packet length distributions. According to this assumption, any traffic correlations can be ignored and the effect on delay performance is negligible, subject to sufficient traffic mixing and moderate-to-heavy traffic loads. In this context, results associated with measurements, traffic modeling and delay analysis of an actual chain of IP routers are reported from experiments conducted at the Blekinge Institute of Technology in Karlskrona, Sweden. It is shown that no experimental evidence was found in support of Kleinrock's independence assumption as traffic correlation has an adverse effect on the end-to-end delay of the tandem queueing system.

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Section: Queueing Delay In Chained Ip Routersmentioning

confidence: 78%

“…On the other hand, under heavy loads, the average delay tends to be dramatically less. A reverse situation is valid under light traffic conditions as well [11].…”

Section: Queueing Delay In Chained Ip Routersmentioning

confidence: 99%

Section: Queueing Delay In Chained Ip Routersmentioning

confidence: 99%

Section: Queueing Delay In Chained Ip Routersmentioning

confidence: 99%

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On Kleinrock’s Independence Assumption

Popescu

Constantinescu²

2011

Network Performance Engineering

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“…However, using SCV as a single measure of the variability of a non-renewal process may result in significant error in the approximation of performance measure. It is shown that the two-moment parametrization that does not account for the autocorrelation is subject to a serious under-approximation of waiting time especially at a bottleneck station in a network with highly variable arrival process or highly variable service process; Fendick, Saksena, and Whitt(1989Whitt( , 1991, Jageman et. al.…”

Section: Introductionmentioning

confidence: 99%

A Simulation Study on the Variability Function of the Arrival Process in Queueing Networks

Kim

2011

Journal of the Korea Society for Simulation

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In queueing network analysis, arrival processes are usually modeled as renewal processes by matching mean and variance. The renewal approximation simplifies the analysis and provides reasonably good estimate for the performance measures of the queueing systems under moderate conditions. However, high variability in arrival process or in service process requires more sophisticated approximation procedures for the variability parameter of departure/arrival processes. In this paper, we propose an heuristic approach to refine Whitt's variability function with the -interval squared coefficient of variation also known as the index of dispersion for intervals(IDI). Regression analysis is used to establish an empirical relationships between the IDI of arrival process and the IDI of departure process of a queueing system.

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Discrete Time Single‐server Queues with Interdependent Interarrival and Service Times

Alfa

2021

Queueing Theory 1

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Dependence in packet queues

Cited by 120 publications

References 32 publications

On Kleinrock’s Independence Assumption

On Kleinrock’s Independence Assumption

A Simulation Study on the Variability Function of the Arrival Process in Queueing Networks

Discrete Time Single‐server Queues with Interdependent Interarrival and Service Times

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