...
首页> 外文期刊>Queueing systems >Transient characteristics of Gaussian queues
【24h】

Transient characteristics of Gaussian queues

机译:高斯排队的暂态特征

获取原文
获取原文并翻译 | 示例
           

摘要

This paper analyzes transient characteristics of Gaussian queues. More specifically, we determine the logarithmic asymptotics of P(Q_0 > pB, Q_(tb) > qB), where Q_t denotes the workload at time t. For any pair (p,q), three regimes can be distinguished: (A) For small values of T, one of the events {Q_0 > pB} and {Q_(tb) > qB} will essentially imply the other. (B) Then there is an intermediate range of values of T for which it is to be expected that both [Q_0 > pB} and {Q_(tb) > qB} are tight (in that none of them essentially implies the other), but that the time epochs 0 and T lie in the same busy period with overwhelming probability. (C) Finally, for large T, still both events are tight, but now they occur in different busy periods with overwhelming probability. For the short-range dependent case, explicit calculations are presented, whereas for the long-range dependent case, structural results are proven.
机译:本文分析了高斯队列的暂态特征。更具体地说,我们确定P(Q_0> pB,Q_(tb)> qB)的对数渐近性,其中Q_t表示时间t的工作量。对于任何一对(p,q),可以区分三种情况:(A)对于较小的T,事件{Q_0> pB}和{Q_(tb)> qB}中的一个实质上将暗示另一个。 (B)然后有一个T值的中间范围,可以预期[Q_0> pB}和{Q_(tb)> qB}都是紧的(因为它们本质上都不暗示另一个),但时间段0和T处于同一繁忙时段,且具有压倒性的可能性。 (C)最后,对于大T,这两个事件仍然很紧,但是现在它们发生在不同的繁忙时段,且具有压倒性的可能性。对于短距离依赖的情况,给出了显式计算,而对于长距离依赖的情况,则证明了结构结果。

著录项

  • 来源
    《Queueing systems》 |2009年第4期|383-409|共27页
  • 作者单位

    Instytut Matematyczny, University of Wroclaw, pl. Grunwaldzki 2/4, 50-384 Wroclaw, Poland;

    rnKorteweg-de Vries Institute for Mathematics, Plantage Muidergracht 24, 1018 TV Amsterdam, The Netherlands;

    rnKorteweg-de Vries Institute for Mathematics, Plantage Muidergracht 24, 1018 TV Amsterdam, The Netherlands CWI, Amsterdam, The Netherlands EURANDOM, Eindhoven, The Netherlands;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    gaussian queues; large deviations; transient behavior;

    机译:高斯队列;偏差大;瞬态行为;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号