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Bandwidth Allocation under End-to-End Percentile Delay Bounds.

机译:端到端百分比延迟范围下的带宽分配。

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摘要

The main objective of this thesis is the estimation of the bandwidth that should be allocated on each link along the path of a flow of IP packets, so that the end-to-end delay D is bounded statistically. That is, D is less than or equal to a given value T with a probability γ. The path through an IP network is depicted by a tandem queueing network of infinite capacity queues, where each queue represents the output port of a router.;We first obtain some results on adding percentiles, and then we propose two different algorithms for calculating end-to-end percentiles, which is then used in a simple search algorithm to obtain the required bandwidth. The first algorithm is based on probabilistic assumptions regarding the arrival process of the packet flow and service times at each node in the tandem queueing network. The second algorithm is based on traces, such as video traces, that consist of a sequence of tuplets, each describing the time of arrival of a packet and its packet length.;In the first algorithm, we assume that the arrival process to the first queue of the queueing network is bursty and correlated and the service times are exponentially distributed. Initially, we assumed an MMPP (Markov-modulated Poisson process) arrival process, and then we extended the algorithm to a MAP2 (two-stage Markov arrival process) arrival process. A MAP can represent a variety of processes that includes, as special cases, the Poisson process, the phase-type renewal processes, the MMPP and superposition of these. No background arrivals were considered at each node, the implication being that the output port scheduler is assumed to be per flow. The proposed algorithm is based on an interpolation between an upper and lower bound obtained by analyzing only the first queue. It is a relatively simple algorithm despite the complexity of the problem, and as shown through extensive comparisons with simulation data that it has a very low relative error. The average error is 1.25% for MMPP and 4.5% for MAP2.;Video traffic is widely expected to account for a large portion of the traffic in future wired and wireless networks. For interactive video the end-to-end delay has to be less than 150 to 200 msec in order to guarantee good QoE. Interestingly enough, little is known about how much bandwidth should be allocated to an interactive video so that a given percentile of the end-to-end delay is satisfied. Using the above algorithm, we obtained the end-to-end percentile for video traffic, by approximating a video trace with a MAP2. Subsequently, the required bandwidth so that a given end-to-end percentile is satisfied is obtained using a simple search algorithm. Three different types of video traces were used, namely, Cisco’s Telepresence, IPTV and WebEx. The approximation of video trace by a MAP2 coupled with the above algorithm gives results with a low relative error, the average relative error is around 6%.;The algorithm described above for calculating a percentile of the end-to-end delay of a video stream, cannot handle the presence of background traffic that competes with the video within the output port of a router. In view of this, we propose an exact and efficient algorithm for calculating any percentile of the end-to-end delay in the presence of background video traffic, assuming that all video flows are characterized by packet traces and an arriving packet keeps its packet length in the entire queueing network. These traces may be a single stream or multiple streams. Packets in each node are served in a FIFO, the implication being that the output port scheduler is assumed to be per class, which more general than the assumption made in the first algorithm. A class could be a DiffServ class where all video packets are queued. Based on this algorithm, the minimum amount of bandwidth required, so that a given percentile of the end-to-end delay is satisfied, is easily obtained using a simple search algorithm.
机译:本文的主要目的是估计应沿着IP数据包流的路径在每个链路上分配的带宽,以使端到端延迟D在统计上受到限制。即,D以概率γ小于或等于给定值T。无限容量队列的串联队列网络描述了通过IP网络的路径,其中每个队列代表路由器的输出端口。;我们首先获得一些关于添加百分位数的结果,然后提出了两种不同的算法来计算端百分位数,然后将其用于简单的搜索算法中以获得所需的带宽。第一种算法基于关于在串联排队网络中每个节点上的数据包流的到达过程和服务时间的概率假设。第二种算法是基于轨迹(例如视频轨迹),它由一系列连音符组成,每个连音符描述了一个数据包的到达时间及其包长。在第一个算法中,我们假设到达第一个算法的过程排队网络的队列是突发性且相关的,服务时间呈指数分布。最初,我们假设是MMPP(马尔可夫调制泊松过程)到达过程,然后将算法扩展到MAP2(两阶段马尔可夫到达过程)到达过程。 MAP可以代表各种过程,在特殊情况下,包括泊松过程,阶段型更新过程,MMPP以及这些过程的叠加。没有在每个节点上考虑后台到达,这意味着输出端口调度程序被假定为按流进行。所提出的算法基于仅通过分析第一队列而获得的上下限之间的插值。尽管存在问题的复杂性,但它是一种相对简单的算法,并且通过与仿真数据进行的广泛比较表明,该算法具有非常低的相对误差。 MMPP的平均误差为1.25%,而MAP2的平均误差为4.5%。广泛预计视频流量将在未来的有线和无线网络中占很大比例。对于交互式视频,端到端延迟必须小于150到200毫秒,以保证良好的QoE。有趣的是,对于为交互式视频分配多少带宽才能满足给定的端到端延迟百分位数知之甚少。使用上述算法,通过用MAP2近似视频轨迹,我们获得了视频流量的端到端百分比。随后,使用简单的搜索算法即可获得所需的带宽,以便满足给定的端到端百分比。使用了三种不同类型的视频跟踪,分别是思科的网真,IPTV和WebEx。通过MAP2结合上述算法对视频轨迹进行逼近,可以得到相对误差较低的结果,平均相对误差约为6%.;上述算法用于计算视频端到端延迟的百分位数流,无法处理与路由器输出端口中的视频竞争的后台流量。有鉴于此,我们提出了一种精确有效的算法,用于在存在背景视频流量的情况下计算端到端延迟的任何百分位数,假设所有视频流均以数据包跟踪为特征,并且到达的数据包保持其数据包长度在整个排队网络中。这些跟踪可以是单个流或多个流。每个节点中的数据包都在FIFO中提供服务,这意味着输出端口调度程序假定为每个类,这比第一种算法中的假定更为笼统。一个类可以是DiffServ类,其中所有视频数据包都已排队。基于此算法,可以使用简单的搜索算法轻松获得所需的最小带宽量,从而满足给定的端到端延迟百分比。

著录项

  • 作者

    Anjum, Bushra.;

  • 作者单位

    North Carolina State University.;

  • 授予单位 North Carolina State University.;
  • 学科 Engineering Computer.;Computer Science.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 160 p.
  • 总页数 160
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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