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End-to-end delay model in computer networks without Kleinrock’s independence assumption
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DOI：10.1007/s11432-025-4863-y.png)
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Abstract
En 中文
The problem of modeling the end-to-end delay in computer networks without Kleinrock’s independence assumption (KIA) has not been solved since 1961. Computer networks are modeled with the following assumptions: packet arrivals are Poisson, packets are routed based on a fixed routing strategy, packet lengths are exponentially distributed and remain unchanged when they traverse from node to node in networks. In this paper, we first introduce a distribution C(p, θ), which generalizes the hypoexponential distribution. Based on this distribution, we develop a computationally simple method to model three end-to-end delay measures, namely the probability distribution functions, the average delay and the jitter of end-to-end delay. We then show that this method provides a “good” prediction about the above delay measures. This is done by simulating a 40-node random network with 1560 packet flows under two network loads: light and high. For those 1560 flows under two network loads, the end-to-end delay distribution functions using our method generally pass the Kolmogorov-Smirnov test at a 5% significance level; the relative errors in our predicted average end-to-end delay and jitter values are all less than 0.066.
Keywords:
queueing networks
dependent service times
end-to-end delay distribution
computer networks
packet-switched networks
Kleinrock’s independence assumption
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