A Framework for Robust Measurement-Based Admission Control

基于测量的鲁棒准入控制框架

• 批准号: 9814567
• 负责人: David Tse
• 金额: $ 19.43万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-03-15 至 2003-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9814567&HistoricalAwards=false
• 关键词: Framework; Robust; Measurement; Based; Admission

Integrated-services networks are expected to carry a class of traffic that has variable bit-rates and requires Quality of Service (QoS) guarantees. One of the main challenges is the provisioning of QoS to users while efficiently sharing network resources through statistical multiplexing. Admission control plays the essential role of limiting the number of flows admitted into the network such that each individual flow obtains the desired QoS. Measurement-based admission control (MBAC) is a practical way of achieving this objective through measuring the current and past variable traffic load in deciding how many flows can be admitted into the network.Many issues have to be understood in the design of robust MBAC schemes. They include:- impact of estimation errors on performance;- effect of flow dynamics such as flow arrivals and departures;- choice of measurement window size.The goal of the proposed project is to establish a unified framework to study these and other issues in MBAC. We wish to obtain a set of guidelines for designing MBACs that are robust over a wide range of system parameters. Our methodology is to obtain insights from the analysis of a set of basic models, which are in turn validated with simulation experiments on real and synthetic traffic sources.The preliminary investigation on a simple bufferless model yields simple expressions for the relevant performance measures as a function of key parameters such as system size, measurement window size, andflow arrival and departure rates. The analysis provides basic insights for answering the questions asked above. One particularly interesting result is the identification of an important parameter ~T_hwhich we call the critical time-scale for the MBAC problem. This parameter quantifies the amount of time a MBAC scheme has to predict into the future to provide good performance, and determine to a large extent the appropriate measurement window size.The research proposes to build on this foundation and extend the framework to study the following issues:- MBAC using aggregate versus individual flow measurements;- MBAC for buffered links;- impact of long-range dependency, multiple time-scale traffic dynamics, and non-stationarities;- MBAC using direct QoS monitoring versus measurements of statistical parameters.

综合业务网络被期望承载具有可变比特率并且需要服务质量（QoS）保证的一类业务。 其中一个主要的挑战是提供服务质量的用户，同时有效地共享网络资源，通过统计复用。 接纳控制起着限制被接纳进入网络的流的数量的重要作用，使得每个单独的流获得期望的QoS。基于测量的接纳控制（Measurement-based Admission Control，MBAC）是一种通过测量当前和过去的可变业务负载来决定有多少流可以被接纳到网络中来实现这一目标的实用方法。它们包括：-估计误差对性能的影响;-流动动力学的影响，如流动到达和离开;-测量窗口大小的选择。拟议项目的目标是建立一个统一的框架，研究这些和其他问题的MBAC。我们希望获得一套指导方针，设计MBAC是强大的系统参数在很大范围内。我们的方法是从一组基本模型的分析中获得见解，这些模型又通过真实的和合成的流量sources.The初步调查上的一个简单的无缓冲模型的仿真实验进行验证，得到简单的表达式作为关键参数，如系统大小，测量窗口大小，andflow到达和离开率的函数的相关性能指标。分析为回答上述问题提供了基本见解。 一个特别有趣的结果是一个重要的参数T_h，我们称之为MBAC问题的临界时间尺度的识别。 该参数量化了MBAC方案必须预测未来以提供良好性能的时间量，并在很大程度上确定适当的测量窗口大小。- 长距离依赖性、多时间尺度业务动态和非平稳性的影响;-使用直接QoS监视与统计参数测量的MBAC。