QUEUE ANALYSIS IN THE G/G/1 SYSTEM BASED ON HYPEREXPONENTIAL DISTRIBUTIONS

M. Buranova
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Abstract

For real-time applications, the change in packet delay, which is usually called delay jitter, is one of the most important parameters of quality of service in modern infocommunication networks when processing multimedia streams, along with the delay and the probability of packet loss. This article discusses approaches to assessing jitter in modern infocommunication networks when processing non-Poissonian traffic in the G/G/1 system. To approximate the system of an arbitrary queue G/G/1, a model based on hyperexponential distributions of the type H2/H2/1 was used. As a processed stream, the implementation of IP network traffic with the absence of mutual correlations between the time intervals between packets and the times of packet processing is used. An important task in this case is to determine the parameters of hyperexponential distributions for the time intervals between packets and packet processing times. The paper presents two methods for determining the parameters of hyperexponential distributions: using the method of moments and using the EM-algorithm. The paper analyzes the influence of the network load factor on the jitter value when using two models for determining the parameters of hyperexponential distributions. This analysis showed a slight increase in jitter with increasing network load both in the case of using the method of moments and in the case of the EM algorithm. It has been determined that the estimates of the jitter values in the case of applying the method of moments and the EM algorithm are quite close in value. The main result of the work is to obtain simple calculation formulas for the analysis of jitter in the G/G/1 system using hyperexponential distributions.
基于超指数分布的g / g /1系统的队列分析
对于实时应用,在现代信息通信网络中处理多媒体流时,数据包延迟的变化,通常被称为延迟抖动,与延迟和丢包概率一起是影响服务质量的最重要参数之一。本文讨论了在G/G/1系统中处理非泊松流量时评估现代信息通信网络抖动的方法。为了逼近任意队列G/G/1的系统,采用了基于H2/H2/1型超指数分布的模型。作为经过处理的流,实现的IP网络流量在数据包之间的时间间隔和数据包处理次数之间没有相互关联。在这种情况下,一个重要的任务是确定数据包之间的时间间隔和数据包处理时间的超指数分布的参数。本文给出了确定超指数分布参数的两种方法:矩量法和em -算法。本文用两种模型确定超指数分布的参数,分析了网络负载因子对抖动值的影响。该分析表明,在使用矩量方法和EM算法的情况下,抖动都随着网络负载的增加而略有增加。结果表明,应用矩量法和EM算法估计的抖动值在数值上非常接近。本工作的主要结果是得到了用超指数分布分析G/G/1系统抖动的简单计算公式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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