Performance analysis of self-similar traffic for future service-oriented internet

Shunfu Jin, Wuyi Yue, N. Tian
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引用次数: 1

Abstract

In this paper, we present a new method to analyze the performance of automatic repeat request (ARQ) schemes in self-similar traffic for the future service-oriented Internet. Taking into account the self-similar traffic of a massive-scale wireless multimedia service, we build a batch arrival queueing model and suppose the batch size is a random variable following Pareto (c, alpha) distribution. Considering the delay in the setting up procedure of a data link, we introduce a setup strategy in this queueing model. Thus a batch arrival Geomxi/G/1 queueing system with setup is built in this paper. We give the formula for performance measures in terms of setup ratio and offered load for different ARQ schemes. Numerical results are given to evaluate the performance of the system and to show influence of the self-similar degree and the delay of the setup procedure on these system performance.
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面向未来服务型互联网的自相似流量性能分析
针对未来面向服务的互联网,提出了一种分析自相似流量下自动重复请求(ARQ)方案性能的新方法。考虑到大规模无线多媒体业务的自相似流量,我们建立了批到达队列模型,并假设批大小是一个服从Pareto (c, alpha)分布的随机变量。考虑到数据链路建立过程中的延迟,在该排队模型中引入了一种建立策略。为此,本文构建了一个带设置的批量到达Geomxi/G/1排队系统。针对不同的ARQ方案,给出了基于设置率和提供负载的性能度量公式。给出了数值结果来评价系统的性能,并说明了自相似度和设置过程的延迟对系统性能的影响。
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