首页> 外文学位 >Queuing analysis and control of long range dependent traffic: Applications to Internet traffic engineering.
【24h】

Queuing analysis and control of long range dependent traffic: Applications to Internet traffic engineering.

机译:远程相关流量的排队分析和控制:在Internet流量工程中的应用。

获取原文
获取原文并翻译 | 示例

摘要

The thesis presents a statistical analysis of Internet backbone traffic, based on traces with levels of aggregation 10 times larger and timestamp accuracy 1000 times better than in previous studies. The first three moments, marginal distributions and correlation structures of packet size, packet inter-arrival time, byte count and packet count, are studied. It is found that highly aggregated Internet backbone traffic is still long-range dependent (LRD) and self-similar (SS). In fact, all time series examined (packet size, inter-arrival time, byte count, packet count) exhibit long-range dependency and self-similarity. In addition to the now classical analysis at large time-scales (>100ms), the research reports the first statistically relevant results on the short-term correlation ([50μs, 10ms]) of byte and packet count processes. The fit of various analytical models to the traffic traces is also studied. The empirical queuing analysis (i.e., feeding a simulated queue with real traces) confirms the long-range dependence detected through direct analysis by showing that the queue behavior at high level of aggregation still diverges greatly from that predicted by Poisson model, but converges to that predicted by the fractional Brownian motion model (fBm). However, the traffic variability decreases as the level of aggregation increases, as shown by the decreased ratio of standard deviation over mean of byte and packet count processes, and by the lightening of the tails of their marginal distributions. With the less variable traffic, a low loss rate can be achieved using a buffer size in the order of milliseconds of link bandwidth.; Expedited Forwarding (EF) Per-Hop Behavior (PHB) in Differentiated Services (Diffserv) is designed to support voice and other real-time applications over the Internet. This thesis studies the steady-state queue overflow probabilities of priority and first-come-first-served (FCFS) queuing systems with hybrid inputs: the Poisson input process modeling voice and the fBm input process modeling general Internet traffic. It is shown that the two queuing systems can achieve almost the same maximum allowed link utilization on OC48 or higher-speed links. The result suggests that Diffserv may not be necessary on properly traffic engineered high-speed backbone links to support VoIP over Internet.; The thesis proposes a new approach to linear minimum-mean-square-error (MMSE) prediction of LRD traffic arrival process. The approach fits a discrete-time fBm (dt-fBm) model to a traffic arrival process.; Finally, the research proposes a prediction-based active queue management mechanism, prediction-based random early detection (PRED). (Abstract shortened by UMI.)
机译:本文提出了对Internet骨干网流量的统计分析,该跟踪基于聚合级别比以前的研究大10倍,时间戳准确度高1000倍的跟踪。研究了数据包大小,数据包到达时间,字节数和数据包数的前三个时刻,边际分布和相关结构。发现高度聚合的Internet骨干网流量仍然依赖于远程(LRD)和自相似(SS)。实际上,所有检查的时间序列(数据包大小,到达时间,字节数,数据包数)都显示出长期依赖性和自相似性。除了现在对大时间尺度(> 100ms)的经典分析之外,该研究还报告了字节和数据包计数过程的短期相关性([50μs,10ms])的第一个统计相关结果。还研究了各种分析模型对交通痕迹的拟合。经验排队分析(即,为模拟队列提供真实的痕迹)证实了通过直接分析检测到的远程依赖性,这表明高聚合级别的队列行为仍然与Poisson模型所预测的行为大相径庭,但收敛到了这一点。由分数布朗运动模型(fBm)预测。但是,流量可变性会随着聚合级别的增加而降低,如标准差与字节和数据包计数过程的平均值之比的降低以及边缘分布尾部的减轻所表明的。对于较少的可变流量,使用链路带宽以毫秒为单位的缓冲区大小可以实现较低的丢失率。区分服务(Diffserv)中的每跳行为快速转发(EF)功能旨在支持Internet上的语音和其他实时应用程序。本文研究了具有混合输入的优先级和先到先服务(FCFS)排队系统的稳态队列溢出概率:泊松输入过程建模语音和fBm输入过程建模通用Internet流量。结果表明,两个排队系统可以在OC48或更高速的链路上实现几乎相同的最大允许链路利用率。结果表明,在经过适当流量工程设计的高速骨干链路上支持Internet上的VoIP可能不需要Diffserv。本文提出了一种新的方法来预测LRD流量到达过程的线性最小均方误差(MMSE)。该方法使离散时间fBm(dt-fBm)模型适合交通到达过程。最后,研究提出了一种基于预测的主动队列管理机制,即基于预测的随机早期检测( PRED )。 (摘要由UMI缩短。)

著录项

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