Internet Engineering Task Force (IETF) N. Duffield
Request for Comments: 6534 AT&T Labs-Research
Category: Standards Track A. Morton
ISSN: 2070-1721 AT&T Labs
J. Sommers
Colgate University
May 2012
Internet Engineering Task Force (IETF) N. Duffield
Request for Comments: 6534 AT&T Labs-Research
Category: Standards Track A. Morton
ISSN: 2070-1721 AT&T Labs
J. Sommers
Colgate University
May 2012
Loss Episode Metrics for IP Performance Metrics (IPPM)
IP性能指标（IPPM）的损失事件指标
Abstract
摘要
The IETF has developed a one-way packet loss metric that measures the loss rate on a Poisson and Periodic probe streams between two hosts. However, the impact of packet loss on applications is, in general, sensitive not just to the average loss rate but also to the way in which packet losses are distributed in loss episodes (i.e., maximal sets of consecutively lost probe packets). This document defines one-way packet loss episode metrics, specifically, the frequency and average duration of loss episodes and a probing methodology under which the loss episode metrics are to be measured.
IETF开发了一种单向丢包度量，用于测量两台主机之间泊松和周期性探测流的丢包率。然而，数据包丢失对应用程序的影响通常不仅对平均丢失率敏感，而且对数据包丢失在丢失事件中的分布方式（即连续丢失的探测数据包的最大集合）也敏感。本文档定义了单向数据包丢失事件度量，特别是丢失事件的频率和平均持续时间，以及测量丢失事件度量的探测方法。
Status of This Memo
关于下段备忘
This is an Internet Standards Track document.
这是一份互联网标准跟踪文件。
This document is a product of the Internet Engineering Task Force (IETF). It represents the consensus of the IETF community. It has received public review and has been approved for publication by the Internet Engineering Steering Group (IESG). Further information on Internet Standards is available in Section 2 of RFC 5741.
本文件是互联网工程任务组（IETF）的产品。它代表了IETF社区的共识。它已经接受了公众审查，并已被互联网工程指导小组（IESG）批准出版。有关互联网标准的更多信息，请参见RFC 5741第2节。
Information about the current status of this document, any errata, and how to provide feedback on it may be obtained at http://www.rfc-editor.org/info/rfc6534.
有关本文件当前状态、任何勘误表以及如何提供反馈的信息，请访问http://www.rfc-editor.org/info/rfc6534.
Copyright Notice
版权公告
Copyright (c) 2012 IETF Trust and the persons identified as the document authors. All rights reserved.
版权所有（c）2012 IETF信托基金和确定为文件作者的人员。版权所有。
This document is subject to BCP 78 and the IETF Trust's Legal Provisions Relating to IETF Documents (http://trustee.ietf.org/license-info) in effect on the date of publication of this document. Please review these documents carefully, as they describe your rights and restrictions with respect to this document. Code Components extracted from this document must
本文件受BCP 78和IETF信托有关IETF文件的法律规定的约束(http://trustee.ietf.org/license-info)自本文件出版之日起生效。请仔细阅读这些文件，因为它们描述了您对本文件的权利和限制。从该文档中提取的代码组件必须
include Simplified BSD License text as described in Section 4.e of the Trust Legal Provisions and are provided without warranty as described in the Simplified BSD License.
包括信托法律条款第4.e节中所述的简化BSD许可证文本，且不提供简化BSD许可证中所述的担保。
This document may contain material from IETF Documents or IETF Contributions published or made publicly available before November 10, 2008. The person(s) controlling the copyright in some of this material may not have granted the IETF Trust the right to allow modifications of such material outside the IETF Standards Process. Without obtaining an adequate license from the person(s) controlling the copyright in such materials, this document may not be modified outside the IETF Standards Process, and derivative works of it may not be created outside the IETF Standards Process, except to format it for publication as an RFC or to translate it into languages other than English.
本文件可能包含2008年11月10日之前发布或公开的IETF文件或IETF贡献中的材料。控制某些材料版权的人员可能未授予IETF信托允许在IETF标准流程之外修改此类材料的权利。在未从控制此类材料版权的人员处获得充分许可的情况下，不得在IETF标准流程之外修改本文件，也不得在IETF标准流程之外创建其衍生作品，除了将其格式化以RFC形式发布或将其翻译成英语以外的其他语言。
Table of Contents
目录
1. Introduction ....................................................4
1.1. Background and Motivation ..................................4
1.1.1. Requirements Language ...............................5
1.2. Loss Episode Metrics and Bi-Packet Probes ..................5
1.3. Outline and Contents .......................................6
2. Singleton Definition for Type-P-One-way Bi-Packet Loss ..........7
2.1. Metric Name ................................................7
2.2. Metric Parameters ..........................................7
2.3. Metric Units ...............................................7
2.4. Metric Definition ..........................................7
2.5. Discussion .................................................8
2.6. Methodologies ..............................................8
2.7. Errors and Uncertainties ...................................8
2.8. Reporting the Metric .......................................8
3. General Definition of Samples for
Type-P-One-way-Bi-Packet-Loss ...................................8
3.1. Metric Name ................................................9
3.2. Metric Parameters ..........................................9
3.3. Metric Units ...............................................9
3.4. Metric Definition ..........................................9
3.5. Discussion .................................................9
3.6. Methodologies .............................................10
3.7. Errors and Uncertainties ..................................10
3.8. Reporting the Metric ......................................10
4. An Active Probing Methodology for Bi-Packet Loss ...............10
4.1. Metric Name ...............................................10
4.2. Metric Parameters .........................................10
4.3. Metric Units ..............................................11
4.4. Metric Definition .........................................11
4.5. Discussion ................................................11
1. Introduction ....................................................4
1.1. Background and Motivation ..................................4
1.1.1. Requirements Language ...............................5
1.2. Loss Episode Metrics and Bi-Packet Probes ..................5
1.3. Outline and Contents .......................................6
2. Singleton Definition for Type-P-One-way Bi-Packet Loss ..........7
2.1. Metric Name ................................................7
2.2. Metric Parameters ..........................................7
2.3. Metric Units ...............................................7
2.4. Metric Definition ..........................................7
2.5. Discussion .................................................8
2.6. Methodologies ..............................................8
2.7. Errors and Uncertainties ...................................8
2.8. Reporting the Metric .......................................8
3. General Definition of Samples for
Type-P-One-way-Bi-Packet-Loss ...................................8
3.1. Metric Name ................................................9
3.2. Metric Parameters ..........................................9
3.3. Metric Units ...............................................9
3.4. Metric Definition ..........................................9
3.5. Discussion .................................................9
3.6. Methodologies .............................................10
3.7. Errors and Uncertainties ..................................10
3.8. Reporting the Metric ......................................10
4. An Active Probing Methodology for Bi-Packet Loss ...............10
4.1. Metric Name ...............................................10
4.2. Metric Parameters .........................................10
4.3. Metric Units ..............................................11
4.4. Metric Definition .........................................11
4.5. Discussion ................................................11
4.6. Methodologies .............................................11
4.7. Errors and Uncertainties ..................................12
4.8. Reporting the Metric ......................................12
5. Loss Episode Proto-Metrics .....................................12
5.1. Loss-Pair-Counts ..........................................13
5.2. Bi-Packet-Loss-Ratio ......................................13
5.3. Bi-Packet-Loss-Episode-Duration-Number ....................13
5.4. Bi-Packet-Loss-Episode-Frequency-Number ...................13
6. Loss Episode Metrics Derived from Bi-Packet Loss Probing .......14
6.1. Geometric Stream: Loss Ratio ..............................14
6.1.1. Metric Name ........................................14
6.1.2. Metric Parameters ..................................14
6.1.3. Metric Units .......................................15
6.1.4. Metric Definition ..................................15
6.1.5. Discussion .........................................15
6.1.6. Methodologies ......................................15
6.1.7. Errors and Uncertainties ...........................15
6.1.8. Reporting the Metric ...............................15
6.2. Geometric Stream: Loss Episode Duration ...................16
6.2.1. Metric Name ........................................16
6.2.2. Metric Parameters ..................................16
6.2.3. Metric Units .......................................16
6.2.4. Metric Definition ..................................16
6.2.5. Discussion .........................................16
6.2.6. Methodologies ......................................16
6.2.7. Errors and Uncertainties ...........................17
6.2.8. Reporting the Metric ...............................17
6.3. Geometric Stream: Loss Episode Frequency ..................17
6.3.1. Metric Name ........................................17
6.3.2. Metric Parameters ..................................17
6.3.3. Metric Units .......................................17
6.3.4. Metric Definition ..................................18
6.3.5. Discussion .........................................18
6.3.6. Methodologies ......................................18
6.3.7. Errors and Uncertainties ...........................18
6.3.8. Reporting the Metric ...............................18
7. Applicability of Loss Episode Metrics ..........................18
7.1. Relation to Gilbert Model .................................18
8. Security Considerations ........................................19
9. References .....................................................20
9.1. Normative References ......................................20
9.2. Informative References ....................................20
4.6. Methodologies .............................................11
4.7. Errors and Uncertainties ..................................12
4.8. Reporting the Metric ......................................12
5. Loss Episode Proto-Metrics .....................................12
5.1. Loss-Pair-Counts ..........................................13
5.2. Bi-Packet-Loss-Ratio ......................................13
5.3. Bi-Packet-Loss-Episode-Duration-Number ....................13
5.4. Bi-Packet-Loss-Episode-Frequency-Number ...................13
6. Loss Episode Metrics Derived from Bi-Packet Loss Probing .......14
6.1. Geometric Stream: Loss Ratio ..............................14
6.1.1. Metric Name ........................................14
6.1.2. Metric Parameters ..................................14
6.1.3. Metric Units .......................................15
6.1.4. Metric Definition ..................................15
6.1.5. Discussion .........................................15
6.1.6. Methodologies ......................................15
6.1.7. Errors and Uncertainties ...........................15
6.1.8. Reporting the Metric ...............................15
6.2. Geometric Stream: Loss Episode Duration ...................16
6.2.1. Metric Name ........................................16
6.2.2. Metric Parameters ..................................16
6.2.3. Metric Units .......................................16
6.2.4. Metric Definition ..................................16
6.2.5. Discussion .........................................16
6.2.6. Methodologies ......................................16
6.2.7. Errors and Uncertainties ...........................17
6.2.8. Reporting the Metric ...............................17
6.3. Geometric Stream: Loss Episode Frequency ..................17
6.3.1. Metric Name ........................................17
6.3.2. Metric Parameters ..................................17
6.3.3. Metric Units .......................................17
6.3.4. Metric Definition ..................................18
6.3.5. Discussion .........................................18
6.3.6. Methodologies ......................................18
6.3.7. Errors and Uncertainties ...........................18
6.3.8. Reporting the Metric ...............................18
7. Applicability of Loss Episode Metrics ..........................18
7.1. Relation to Gilbert Model .................................18
8. Security Considerations ........................................19
9. References .....................................................20
9.1. Normative References ......................................20
9.2. Informative References ....................................20
Packet loss in the Internet is a complex phenomenon due to the bursty nature of traffic and congestion processes, influenced by both end-users and applications and the operation of transport protocols such as TCP. For these reasons, the simplest model of packet loss -- the single parameter Bernoulli (independent) loss model -- does not represent the complexity of packet loss over periods of time. Correspondingly, a single loss metric -- the average packet loss ratio over some period of time -- arising, e.g., from a stream of Poisson probes as in [RFC2680] is not sufficient to determine the effect of packet loss on traffic in general.
由于流量和拥塞过程的突发性，互联网中的数据包丢失是一种复杂的现象，受最终用户和应用程序以及传输协议（如TCP）操作的影响。由于这些原因，最简单的数据包丢失模型——单参数贝努利（独立）丢失模型——并不代表数据包在一段时间内丢失的复杂性。相应地，如[RFC2680]中的泊松探测流所产生的单个丢失度量（一段时间内的平均分组丢失率）不足以确定分组丢失对一般通信量的影响。
Moving beyond single parameter loss models, Markovian and Markov-modulated loss models involving transitions between a good and bad state, each with an associated loss rate, have been proposed by Gilbert [Gilbert] and more generally by Elliot [Elliot]. In principle, Markovian models can be formulated over state spaces involving patterns of loss of any desired number of packets. However, further increase in the size of the state space makes such models cumbersome both for parameter estimation (accuracy decreases) and prediction in practice (due to computational complexity and sensitivity to parameter inaccuracy). In general, the relevance and importance of particular models can change in time, e.g., in response to the advent of new applications and services. For this reason, we are drawn to empirical metrics that do not depend on a particular model for their interpretation.
Gilbert[Gilbert]和Elliot[Elliot]提出了超越单参数损失模型的马尔可夫和马尔可夫调制损失模型，涉及好状态和坏状态之间的转换，每个模型都有相关的损失率。原则上，马尔可夫模型可以在状态空间上建立，包括任意数量的数据包的丢失模式。然而，状态空间大小的进一步增加使得此类模型在参数估计（精度降低）和实际预测（由于计算复杂性和对参数不准确的敏感性）方面都很麻烦。一般来说，特定模型的相关性和重要性可能会随着时间而变化，例如，随着新应用程序和服务的出现。出于这个原因，我们被吸引到不依赖于特定模型进行解释的经验指标。
An empirical measure of packet loss complexity, the index of dispersion of counts (IDC), comprise, for each t >0, the ratio v(t) / a(t) of the variance v(t) and average a(t) of the number of losses over successive measurement windows of a duration t. However, a full characterization of packet loss over time requires specification of the IDC for each window size t>0.
分组丢失复杂性的经验度量，即计数分散指数（IDC），对于每个t>0，包括方差v（t）的比率v（t）/a（t）和持续时间t的连续测量窗口中丢失数量的平均a（t）。然而，要全面描述数据包随时间的丢失情况，需要为每个窗口大小t>0指定IDC。
In the standards arena, loss pattern sample metrics are defined in [RFC3357]. Following the Gilbert-Elliot model, burst metrics specific for Voice over IP (VoIP) that characterize complete episodes of lost, transmitted, and discarded packets are defined in [RFC3611].
在标准领域，[RFC3357]中定义了损耗模式样本度量。按照Gilbert-Elliot模型，在[RFC3611]中定义了IP语音（VoIP）的突发度量，该度量表征丢失、传输和丢弃数据包的完整事件。
The above considerations motivate the formulation of empirical metrics of one-way packet loss that provide the simplest generalization of [RFC2680] (which is widely adopted but only defines a single loss-to-total ratio metric). The metrics defined here
上述考虑促使制定单向分组丢失的经验度量，该度量提供了[RFC2680]的最简单概括（该度量被广泛采用，但仅定义了单个丢失与总比率度量）。这里定义的指标
capture deviations from independent packet loss in a robust model-independent manner. The document also defines efficient measurement methodologies for these metrics.
以稳健的模型独立方式捕获独立数据包丢失的偏差。该文件还定义了这些指标的有效测量方法。
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this document are to be interpreted as described in RFC 2119 [RFC2119].
本文件中的关键词“必须”、“不得”、“要求”、“应”、“不应”、“应”、“不应”、“建议”、“可”和“可选”应按照RFC 2119[RFC2119]中所述进行解释。
The losses experienced by the packet stream can be viewed as occurring in loss episodes, i.e., a maximal set of consecutively lost packets. This memo describes one-way loss episode metrics: their frequency and average duration. Although the average loss ratio can be expressed in terms of these quantities, they go further in characterizing the statistics of the patterns of packet loss within the stream of probes. This is useful information in understanding the effect of packet losses on application performance, since different applications can have different sensitivities to patterns of loss, being sensitive not only to the long-term average loss rate, but how losses are distributed in time. As an example, MPEG video traffic may be sensitive to loss involving the I-frame in a group of pictures, but further losses within an episode of sufficiently short duration have no further impact; the damage is already done.
分组流经历的丢失可被视为发生在丢失事件中，即，连续丢失分组的最大集合。本备忘录描述了单向损失事件指标：频率和平均持续时间。虽然平均丢失率可以用这些数量表示，但它们进一步描述了探测流中的分组丢失模式的统计特性。这对于理解数据包丢失对应用程序性能的影响非常有用，因为不同的应用程序可能对丢失模式具有不同的敏感性，不仅对长期平均丢失率敏感，而且对丢失在时间上的分布方式也敏感。例如，MPEG视频流量可能对涉及图片组中的I帧的丢失敏感，但是在足够短的持续时间内的片段内的进一步丢失没有进一步的影响；损害已经造成了。
The loss episode metrics presented here have the following useful properties:
此处提供的损失事件度量具有以下有用属性：
1. the metrics are empirical and do not depend on an underlying model; e.g., the loss process is not assumed to be Markovian. On the other hand, it turns out that the metrics of this memo can be related to the special case of the Gilbert Model parameters; see Section 7.
1. 这些指标是经验性的，不依赖于基础模型；e、 假设损失过程不是马尔可夫过程。另一方面，事实证明，本备忘录的指标可能与吉尔伯特模型参数的特殊情况有关；见第7节。
2. the metric units can be directly compared with applications or user requirements or tolerance for network loss performance, in the frequency and duration of loss episodes, as well as the usual packet loss ratio, which can be recovered from the loss episode metrics upon dividing the average loss episode duration by the loss episode frequency.
2. 度量单位可以直接与应用程序或用户需求或网络丢失性能容差进行比较，包括丢失事件的频率和持续时间，以及通常的分组丢失率，在将平均丢失事件持续时间除以丢失事件频率后，可以从丢失事件度量中恢复。
3. the metrics provide the smallest possible increment in complexity beyond, but in the spirit of, the IP Performance Metrics (IPPM) average packet loss ratio metrics [RFC2680], i.e., moving from a single metric (average packet loss ratio) to a pair of metrics (loss episode frequency and average loss episode duration).
3. 这些度量提供了超出IP性能度量（IPPM）平均分组丢失率度量[RFC2680]的最小可能复杂性增量，即从单个度量（平均分组丢失率）移动到一对度量（丢失事件频率和平均丢失事件持续时间）。
The document also describes a probing methodology under which loss episode metrics are to be measured. The methodology comprises sending probe packets in pairs, where packets within each probe pair have a fixed separation, and the time between pairs takes the form of a geometric distributed number multiplied by the same separation. This can be regarded a generalization of Poisson probing where the probes are pairs rather than single packets as in [RFC2680], and also of geometric probing described in [RFC2330]. However, it should be distinguished from back-to-back packet pairs whose change in separation on traversing a link is used to probe bandwidth. In this document, the separation between the packets in a pair is the temporal resolution at which different loss episodes are to be distinguished. The methodology does not measure episodes of loss of consecutive background packets on the measured path. One key feature of this methodology is its efficiency: it estimates the average length of loss episodes without directly measuring the complete episodes themselves. Instead, this information is encoded in the observed relative frequencies of the four possible outcomes arising from the loss or successful transmission of each of the two packets of the probe pairs. This is distinct from the approach of [RFC3611], which reports on directly measured episodes.
本文件还描述了一种探测方法，在该方法下，将对损失事件指标进行测量。该方法包括成对发送探测数据包，其中每个探测数据包对内的数据包具有固定的间隔，并且对之间的时间采用几何分布数乘以相同间隔的形式。这可以被视为泊松探测的推广，其中探测是成对的，而不是[RFC2680]中所述的单个数据包，以及[RFC2330]中所述的几何探测。然而，它应该区别于背对背分组对，背对背分组对在穿越链路时分离的变化用于探测带宽。在本文档中，成对分组之间的分离是区分不同丢失事件的时间分辨率。该方法不测量所测量路径上连续背景数据包的丢失事件。这种方法的一个关键特征是它的效率：它估计损失事件的平均长度，而不直接测量完整事件本身。相反，该信息被编码在四种可能结果的观测相对频率中，这四种可能结果是由探针对的两个分组中的每一个的丢失或成功传输引起的。这与[RFC3611]的方法不同，后者报告直接测量的事件。
The metrics defined in this memo are "derived metrics", according to Section 6.1 of [RFC2330] (the IPPM framework). They are based on the singleton loss metric defined in Section 2 of [RFC2680] .
根据[RFC2330]（IPPM框架）第6.1节，本备忘录中定义的指标为“衍生指标”。它们基于[RFC2680]第2节中定义的单件损耗指标。
o Section 2 defines the fundamental singleton metric for the possible outcomes of a probe pair: Type-P-One-way-Bi-Packet-Loss.
o 第2节定义了探测对可能结果的基本单例度量：Type-P-One-way-Bi-Packet-Loss。
o Section 3 defines sample sets of this metric derived from a general probe stream: Type-P-One-way-Bi-Packet-Loss-Stream.
o 第3节定义了该度量的样本集，该样本集源自一般探测流：Type-P-One-way-Bi-Packet-Loss-stream。
o Section 4 defines the prime example of the Bi-Packet-Loss-Stream metrics, specifically Type-P-One-way-Bi-Packet-Loss-Geometric-Stream arising from the geometric stream of packet-pair probes that was described informally in Section 1.
o 第4节定义了Bi分组丢失流度量的主要示例，特别是第1节非正式描述的分组对探测的几何流产生的类型-P-单向-Bi-分组丢失-Geometric-Stream。
o Section 5 defines loss episode proto-metrics that summarize the outcomes from a stream metrics as an intermediate step to forming the loss episode metrics; they need not be reported in general.
o 第5节定义了损失插曲原型指标，该指标总结了流指标的结果，作为形成损失插曲指标的中间步骤；一般情况下不需要报告这些情况。
o Section 6 defines the final loss episode metrics that are the focus of this memo, the new metrics:
o 第6节定义了本备忘录关注的最终损失事件指标，即新指标：
* Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Episode-Duration, the average duration, in seconds, of a loss episode.
* Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-spice-Duration，丢失事件的平均持续时间，以秒为单位。
* Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Episode-Frequency, the average frequency, per second, at which loss episodes start.
* Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-spice-Frequency，丢失事件开始的平均频率（每秒）。
* Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Ratio, which is the average packet loss ratio metric arising from the geometric stream probing methodology
* Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Ratio，它是由几何流探测方法产生的平均分组丢失率度量
o Section 7 details applications and relations to existing loss models.
o 第7节详细介绍了应用程序以及与现有损失模型的关系。
Type-P-One-way-Bi-Packet-Loss
P型单向双丢包
o Src, the IP address of a source host
o Src，源主机的IP地址
o Dst, the IP address of a destination host
o Dst，目标主机的IP地址
o T1, a sending time of the first packet
o T1，第一分组的发送时间
o T2, a sending time of the second packet, with T2>T1
o T2，第二分组的发送时间，T2>T1
o F, a selection function defining unambiguously the two packets from the stream selected for the metric
o F、 一个选择函数，明确定义为度量选择的流中的两个数据包
o P, the specification of the packet type, over and above the source and destination addresses
o P、 在源地址和目标地址之上的数据包类型规范
A Loss Pair is pair (l1, l2) where each of l1 and l2 is a binary value 0 or 1, where 0 signifies successful transmission of a packet and 1 signifies loss.
丢失对是对（l1，l2），其中l1和l2中的每一个都是二进制值0或1，其中0表示成功传输分组，1表示丢失。
The metric unit of Type-P-One-way-Bi-Packet-Loss is a Loss Pair.
P-One-way-Bi-Packet-Loss类型的度量单位是丢失对。
1. "The Type-P-One-way-Bi-Packet-Loss with parameters (Src, Dst, T1, T2, F, P) is (1,1)" means that Src sent the first bit of a Type-P packet to Dst at wire-time T1 and the first bit of a Type-P packet to Dst at wire-time T2>T1 and that neither packet was received at Dst.
1. “带参数（Src，Dst，T1，T2，F，P）的P型单向双分组丢失为（1,1）”意味着Src在连线时间T1向Dst发送P型分组的第一位，在连线时间T2>T1向Dst发送P型分组的第一位，并且在Dst未接收到任何分组。
2. "The Type-P-One-way-Bi-Packet-Loss with parameters (Src, Dst, T1, T2, F, P) is (1,0)" means that Src sent the first bit of a Type-P packet to Dst at wire-time T1 and the first bit of a Type-P packet to Dst at wire-time T2>T1 and that the first packet was not received at Dst, and the second packet was received at Dst
2. “带参数（Src、Dst、T1、T2、F、P）的P型单向双分组丢失为（1,0）”意味着Src在连线时间T1向Dst发送P型分组的第一位，在连线时间T2>T1向Dst发送P型分组的第一位，并且在Dst未接收到第一个分组，在Dst接收到第二个分组
3. "The Type-P-One-way-Bi-Packet-Loss with parameters (Src, Dst, T1, T2, F, P) is (0,1)" means that Src sent the first bit of a Type-P packet to Dst at wire-time T1 and the first bit of a Type-P packet to Dst at wire-time T2>T1 and that the first packet was received at Dst, and the second packet was not received at Dst
3. “带参数（Src、Dst、T1、T2、F、P）的P型单向双分组丢失为（0,1）”意味着Src在连线时间T1向Dst发送P型分组的第一位，在连线时间T2>T1向Dst发送P型分组的第一位，并且第一个分组在Dst接收，第二个分组在Dst未接收
4. "The Type-P-One-way-Bi-Packet-Loss with parameters (Src, Dst, T1, T2, F, P) is (0,0)" means that Src sent the first bit of a Type-P packet to Dst at wire-time T1 and the first bit of a Type-P packet to Dst at wire-time T2>T1 and that both packets were received at Dst.
4. “带参数（Src、Dst、T1、T2、F、P）的P型单向双分组丢失为（0,0）”意味着Src在连线时间T1向Dst发送P型分组的第一位，在连线时间T2>T1向Dst发送P型分组的第一位，并且在Dst接收两个分组。
The purpose of the selection function is to specify exactly which packets are to be used for measurement. The notion is taken from Section 2.5 of [RFC3393], where examples are discussed.
选择函数的目的是精确指定用于测量的数据包。该概念取自[RFC3393]第2.5节，其中讨论了示例。
The methodologies related to the Type-P-One-way-Packet-Loss metric in Section 2.6 of [RFC2680] are similar for the Type-P-One-way-Bi-Packet-Loss metric described above. In particular, the methodologies described in RFC 2680 apply to both packets of the pair.
[RFC2680]第2.6节中与P型单向丢包度量相关的方法与上述P型单向双丢包度量类似。具体地，RFC 2680中描述的方法适用于该对的两个分组。
Sources of error for the Type-P-One-way-Packet-Loss metric in Section 2.7 of [RFC2680] apply to each packet of the pair for the Type-P-One-way-Bi-Packet-Loss metric.
[RFC2680]第2.7节中的P型单向分组丢失度量的错误源适用于P型单向双分组丢失度量对中的每个分组。
Refer to Section 2.8 of [RFC2680].
参考[RFC2680]第2.8节。
Given the singleton metric for Type-P-One-way-Bi-Packet-Loss, we now define examples of samples of singletons. The basic idea is as follows. We first specify a set of times T1 < T2 <...<Tn, each of
给定P型单向双包丢失的单例度量，我们现在定义单例示例。基本思路如下。我们首先指定一组时间T1<T2<…<Tn，每个时间
which acts as the first time of a packet pair for a single Type-P-One-way-Bi-Packet-Loss measurement. This results is a set of n metric values of Type-P-One-way-Bi-Packet-Loss.
作为单个类型P单向双丢包测量的数据包对的第一次。该结果是一组类型为P-单向-Bi-分组丢失的n个度量值。
Type-P-One-way-Bi-Packet-Loss-Stream
P型单向双丢包流
o Src, the IP address of a source host
o Src，源主机的IP地址
o Dst, the IP address of a destination host
o Dst，目标主机的IP地址
o (T11,T12), (T21,T22)....,(Tn1,Tn2) a set of n times of sending
times for packet pairs, with T11 < T12 <= T21 < T22 <=...<= Tn1 <
Tn2
o (T11,T12), (T21,T22)....,(Tn1,Tn2) a set of n times of sending
times for packet pairs, with T11 < T12 <= T21 < T22 <=...<= Tn1 <
Tn2
o F, a selection function defining unambiguously the two packets from the stream selected for the metric
o F、 一个选择函数，明确定义为度量选择的流中的两个数据包
o P, the specification of the packet type, over and above the source and destination address
o P、 数据包类型的说明，在源地址和目标地址之上
A set L1,L2,...,Ln of Loss Pairs
损失对的集合L1，L2，…，Ln
Each Loss Pair Li for i = 1,....n is the Type-P-One-way-Bi-Packet-
Loss with parameters (Src, Dst, Ti1, Ti2, Fi, P) where Fi is the
restriction of the selection function F to the packet pair at time
Ti1, Ti2.
Each Loss Pair Li for i = 1,....n is the Type-P-One-way-Bi-Packet-
Loss with parameters (Src, Dst, Ti1, Ti2, Fi, P) where Fi is the
restriction of the selection function F to the packet pair at time
Ti1, Ti2.
The metric definition of Type-P-One-way-Bi-Packet-Loss-Stream is sufficiently general to describe the case where packets are sampled from a preexisting stream. This is useful in the case in which there is a general purpose measurement stream set up between two hosts, and we wish to select a substream from it for the purposes of loss episode measurement. Packet pairs selected as bi-packet loss probes need not be consecutive within such a stream. In the next section, we specialize this somewhat to more concretely describe a purpose built packet stream for loss episode measurement.
P-单向-Bi-分组丢失流类型的度量定义足够一般，以描述从先前存在的流中采样分组的情况。这在两台主机之间建立了通用测量流的情况下非常有用，我们希望从中选择一个子流以进行损失测量。被选择为bi分组丢失探测的分组对在这样的流中不需要是连续的。在下一节中，我们将对此进行专门化，以便更具体地描述一个专门构建的用于丢失事件测量的数据包流。
The methodologies related to the Type-P-One-way-Packet-Loss metric in Section 2.6 of [RFC2680] are similar for the Type-P-One-way-Bi-Packet-Loss-Stream metric described above. In particular, the methodologies described in RFC 2680 apply to both packets of each pair.
[RFC2680]第2.6节中与P型单向丢包度量相关的方法与上述P型单向双丢包流度量类似。具体而言，RFC 2680中描述的方法适用于每对的两个分组。
Sources of error for the Type-P-One-way-Packet-Loss metric in Section 2.7 of [RFC2680] apply to each packet of each pair for the Type-P-One-way-Bi-Packet-Loss-Stream metric.
[RFC2680]第2.7节中类型P单向分组丢失度量的错误源适用于类型P单向双分组丢失流度量的每对数据包。
Refer to Section 2.8 of [RFC2680].
参考[RFC2680]第2.8节。
This section specializes the preceding section for an active probing methodology. The basic idea is a follows. We set up a sequence of evenly spaced times T1 < T2 < ... < Tn. Each time Ti is potentially the first packet time for a packet pair measurement. We make an independent random decision at each time, whether to initiate such a measurement. Hence, the interval count between successive times at which a pair is initiated follows a geometric distribution. We also specify that the spacing between successive times Ti is the same as the spacing between packets in a given pair. Thus, if pairs happen to be launched at the successive times Ti and T(i+1), the second packet of the first pair is actually used as the first packet of the second pair.
本节专门介绍前一节中的主动探测方法。基本思想如下。我们建立了一个等间隔时间序列T1<T2<…<Tn.每次Ti可能是分组对测量的第一个分组时间。我们每次都会做出一个独立的随机决定，决定是否启动这样的测量。因此，启动配对的连续时间之间的间隔计数遵循几何分布。我们还指定连续时间Ti之间的间隔与给定对中的数据包之间的间隔相同。因此，如果配对恰好在连续时间Ti和T（i+1）启动，则第一对的第二分组实际用作第二对的第一分组。
Type-P-One-way-Bi-Packet-Loss-Geometric-Stream
类型-P-单向-Bi-丢包-P-流
o Src, the IP address of a source host
o Src，源主机的IP地址
o Dst, the IP address of a destination host
o Dst，目标主机的IP地址
o T0, the randomly selected starting time [RFC3432] for periodic launch opportunities
o T0，随机选择的周期性发射机会的开始时间[RFC3432]
o d, the time spacing between potential launch times, Ti and T(i+1)
o d、 潜在发射时间Ti和T（i+1）之间的时间间隔
o n, a count of potential measurement instants
o n、 潜在测量瞬间的计数
o q, a launch probability
o q、 发射概率
o F, a selection function defining unambiguously the two packets from the stream selected for the metric
o F、 一个选择函数，明确定义为度量选择的流中的两个数据包
o P, the specification of the packet type, over and above the source and destination address
o P、 数据包类型的说明，在源地址和目标地址之上
A set of Loss Pairs L1, L2, ..., Lm for some m <= n
一组损失对L1，L2，…，Lm，对于某些m<=n
For each i = 0, 1, ..., n-1 we form the potential measurement time Ti = T0 + i*d. With probability q, a packet pair measurement is launched at Ti, resulting in a Type-P-One-way-Bi-Packet-Loss with parameters (Src, Dst, Ti, T(i+1), Fi, P) where Fi is the restriction of the selection function F to the packet pair at times Ti, T(i+1). L1, L2,...Lm are the resulting Loss Pairs; m can be less than n since not all times Ti have an associated measurement.
对于每个i=0，1，…，n-1，我们形成电位测量时间Ti=T0+i*d。利用概率q，在Ti处发起分组对测量，导致具有参数（Src、Dst、Ti、T（i+1）、Fi、P）的P型单向双分组丢失，其中Fi是在时间Ti、T（i+1）对分组对的选择函数F的限制。L1，L2，…Lm是产生的损耗对；m可以小于n，因为并非所有时间Ti都有相关测量。
The above definition of Type-P-One-way-Bi-Packet-Loss-Geometric-Stream is equivalent to using Type-P-One-way-Bi-Packet-Loss-Stream with an appropriate statistical definition of the selection function F.
P-One-way-Bi-Packet-Loss-Geometric-Stream类型的上述定义等同于使用具有选择函数F的适当统计定义的P-One-way-Bi-Packet-Loss-Stream类型。
The number m of Loss Pairs in the metric can be less than the number of potential measurement instants because not all instants may generate a probe when the launch probability q is strictly less than 1.
度量中损失对的数量m可以小于潜在测量瞬间的数量，因为当发射概率q严格小于1时，并非所有瞬间都会生成探测。
The methodologies follow from:
方法如下：
o the specific time T0, from which all successive Ti follow, and
o 特定时间T0，从该时间开始，所有连续Ti跟随，以及
o the specific time spacing, and
o 具体的时间间隔，以及
o the methodologies discussion given above for the singleton Type-P-One-way-Bi-Packet-Loss metric.
o 上文给出的单例类型-P-单向-Bi-分组丢失度量的方法论讨论。
The issue of choosing an appropriate time spacing (e.g., one that is matched to expected characteristics of loss episodes) is outside the scope of this document.
选择适当的时间间隔（例如，与损失事件的预期特征相匹配的时间间隔）的问题不在本文件的范围内。
Note that as with any active measurement methodology, consideration must be made to handle out-of-order arrival of packets; see also Section 3.6. of [RFC2680].
注意，与任何主动测量方法一样，必须考虑处理数据包的无序到达；另见第3.6节。属于[RFC2680]。
In addition to sources of errors and uncertainties related to methodologies for measuring the singleton Type-P-One-way-Bi-Packet-Loss metric, a key source of error when emitting packets for Bi-Packet Loss relates to resource limits on the host used to send the packets. In particular, the choice of T0, the choice of the time spacing, and the choice of the launch probability results in a schedule for sending packets. Insufficient CPU resources on the sending host may result in an inability to send packets according to schedule. Note that the choice of time spacing directly affects the ability of the host CPU to meet the required schedule (e.g., consider a 100 microsecond spacing versus a 100 millisecond spacing).
除了与测量singleton Type-P-One-way-Bi-Packet-Loss度量的方法相关的错误和不确定性的来源之外，当发送用于Bi-Packet-Loss的包时，一个关键的错误来源与用于发送包的主机上的资源限制有关。具体地，T0的选择、时间间隔的选择和发射概率的选择导致用于发送分组的调度。发送主机上的CPU资源不足可能导致无法按照计划发送数据包。注意，时间间隔的选择直接影响主机CPU满足所需时间表的能力（例如，考虑100微秒间距与100毫秒间距）。
For other considerations, refer to Section 3.7 of [RFC2680].
有关其他注意事项，请参考[RFC2680]第3.7节。
Refer to Section 3.8. of [RFC2680].
参考第3.8节。属于[RFC2680]。
This section describes four generic proto-metric quantities associated with an arbitrary set of Loss Pairs. These are the Loss-Pair-Counts, Bi-Packet-Loss-Ratio, Bi-Packet-Loss-Episode-Duration-Number, Bi-Packet-Loss-Episode-Frequency-Number. Specific loss episode metrics can then be constructed when these proto-metrics take, as their input, sets of Loss Pairs samples generated by the Type-P-One-way-Bi-Packet-Loss-Stream and Type-P-One-way-Bi-Packet-Loss-Geometric-Stream. The second of these is described in Section 4. It is not expected that these proto-metrics would be reported themselves. Rather, they are intermediate quantities in the production of the final metrics of Section 6 below, and could be rolled up into metrics in implementations. The metrics report loss episode durations and frequencies in terms of packet counts, since they do not depend on the actual time between probe packets. The final metrics of Section 6 incorporate timescales and yield durations in seconds and frequencies as per second.
本节描述了与任意一组损耗对相关的四个通用原型度量量。这些是丢失对计数、Bi分组丢失率、Bi分组丢失事件持续时间数、Bi分组丢失事件频率数。然后，当这些原型度量采用由Type-P-One-way-Bi-Packet-loss-Stream和Type-P-One-way-Bi-Packet-loss-Stream生成的丢失对样本集作为其输入时，可以构造特定的丢失事件度量。第4节介绍了第二种方法。预计这些原型指标不会自行报告。相反，它们是下面第6节最终度量的生成过程中的中间数量，可以在实现中汇总为度量。这些指标根据数据包计数报告丢失事件持续时间和频率，因为它们不依赖于探测数据包之间的实际时间。第6节的最终指标包括以秒为单位的时间尺度和产量持续时间，以及以秒为单位的频率。
Loss-Pair-Counts are the absolute frequencies of the four types of Loss Pair outcome in a sample. More precisely, the Loss-Pair-Counts associated with a set of Loss Pairs L1,,,,Ln are the numbers N(i,j) of such Loss Pairs that take each possible value (i,j) in the set ( (0,0), (0,1), (1,0), (1,1)).
损失对计数是样本中四种类型的损失对结果的绝对频率。更准确地说，与一组损失对L1、、、Ln相关联的损失对计数是这些损失对的数字N（i，j），这些损失对取集合（（0,0）、（0,1）、（1,0）、（1,1））中的每个可能值（i，j）。
The Bi-Packet-Loss-Ratio associated with a set of n Loss Pairs L1,,,,Ln is defined in terms of their Loss-Pair-Counts by the quantity (N(1,0) + N(1,1))/n.
与一组n个丢失对L1、、、Ln相关联的双分组丢失率根据其丢失对计数由数量（n（1,0）+n（1,1））/n定义。
Note this is formally equivalent to the loss metric Type-P-One-way-Packet-Loss-Average from [RFC2680], since it averages single packet losses.
注：这在形式上等同于[RFC2680]中的损失度量类型-P-单向-分组-丢失-平均值，因为它平均单个分组的损失。
The Bi-Packet-Loss-Episode-Duration-Number associated with a set of n Loss Pairs L1,,,,Ln is defined in terms of their Loss-Pair-Counts in the following cases:
与一组n个丢失对L1、、、Ln相关联的Bi分组丢失事件持续时间编号是根据以下情况下的丢失对计数定义的：
o (2*N(1,1) + N(0,1) + N(1,0)) / (N(0,1) + N(1,0)) if N(0,1) +
N(1,0) > 0
o (2*N(1,1) + N(0,1) + N(1,0)) / (N(0,1) + N(1,0)) if N(0,1) +
N(1,0) > 0
o 0 if N(0,1) + N(1,0) + N(1,1) = 0 (no probe packets lost)
o 0 if N(0,1) + N(1,0) + N(1,1) = 0 (no probe packets lost)
o Undefined if N(0,1) + N(1,0) + N(0,0) = 0 (all probe packets lost)
o 如果N（0,1）+N（1,0）+N（0,0）=0（所有探测数据包丢失），则未定义
Note N(0,1) + N(1,0) is zero if there are no transitions between loss and no-loss outcomes.
注：如果损失和无损失结果之间没有过渡，则N（0,1）+N（1,0）为零。
The Bi-Packet-Loss-Episode-Frequency-Number associated with a set of n Loss Pairs L1,,,,Ln is defined in terms of their Loss-Pair-Counts as Bi-Packet-Loss-Ratio / Bi-Packet-Loss-Episode-Duration-Number, when this can be defined, specifically, it is as follows:
与一组n个丢失对L1、、、Ln相关联的Bi分组丢失集频率编号根据其丢失对计数定义为Bi分组丢失率/Bi分组丢失集持续时间编号，当可以定义时，具体如下：
o (N(1,0) + N(1,1)) * (N(0,1) + N(1,0)) / (2*N(1,1) + N(0,1) +
N(1,0) ) / n if N(0,1) + N(1,0) > 0
o (N(1,0) + N(1,1)) * (N(0,1) + N(1,0)) / (2*N(1,1) + N(0,1) +
N(1,0) ) / n if N(0,1) + N(1,0) > 0
o 0 if N(0,1) + N(1,0) + N(1,1) = 0 (no probe packets lost)
o 0 if N(0,1) + N(1,0) + N(1,1) = 0 (no probe packets lost)
o 1 if N(0,1) + N(1,0) + N(0,0) = 0 (all probe packets lost)
o 1 if N(0,1) + N(1,0) + N(0,0) = 0 (all probe packets lost)
Metrics for the time frequency and time duration of loss episodes are
now defined as functions of the set of n Loss Pairs L1,....,Ln.
Although a loss episode is defined as a maximal set of successive
lost packets, the loss episode metrics are not defined directly in
terms of the sequential patterns of packet loss exhibited by Loss
Pairs. This is because samples, including Type-P-One-way-Bi-Packet-
Loss-Geometric-Stream, generally do not report all lost packets in
each episode. Instead, the metrics are defined as functions of the
Loss-Pair-Counts of the sample, for reasons that are now described.
Metrics for the time frequency and time duration of loss episodes are
now defined as functions of the set of n Loss Pairs L1,....,Ln.
Although a loss episode is defined as a maximal set of successive
lost packets, the loss episode metrics are not defined directly in
terms of the sequential patterns of packet loss exhibited by Loss
Pairs. This is because samples, including Type-P-One-way-Bi-Packet-
Loss-Geometric-Stream, generally do not report all lost packets in
each episode. Instead, the metrics are defined as functions of the
Loss-Pair-Counts of the sample, for reasons that are now described.
Consider an idealized Type-P-One-way-Bi-Packet-Loss-Geometric-Stream sample in which the launch probability q =1. It is shown in [SBDR08] that the average number of packets in a loss episode of this ideal sample is exactly the Bi-Packet-Loss-Episode-Duration derived from its set of Loss Pairs. Note this computation makes no reference to the position of lost packet in the sequence of probes.
考虑一个理想化的类型p一路双向包-几何-流样本，其中发射概率q＝1。[SBDR08]中显示，该理想样本的丢失插曲中的平均数据包数正是从其丢失对集导出的Bi数据包丢失插曲持续时间。注：此计算不参考丢失数据包在探测序列中的位置。
A general Type-P-One-way-Bi-Packet-Loss-Geometric-Stream sample with launch probability q < 1, independently samples, with probability q, each Loss Pair of an idealized sample. On average, the Loss-Pair-Counts (if normalized by the total number of pairs) will be the same as in the idealized sample. The loss episode metrics in the general case are thus estimators of those for the idealized case; the statistical properties of this estimation, including a derivation of the estimation variance, is provided in [SBDR08].
发射概率q<1的一般类型P-单向双分组丢失-几何流样本，独立样本，概率q，每个丢失对为理想样本。平均而言，损失对计数（如果按总对数标准化）将与理想化样本中的相同。因此，一般情况下的损失事件度量是理想情况下损失事件度量的估计量；[SBDR08]中提供了该估计的统计特性，包括估计方差的推导。
Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Ratio
类型-P-单向-双包-丢失-几何-流比率
o Src, the IP address of a source host
o Src，源主机的IP地址
o Dst, the IP address of a destination host
o Dst，目标主机的IP地址
o T0, the randomly selected starting time [RFC3432] for periodic launch opportunities
o T0，随机选择的周期性发射机会的开始时间[RFC3432]
o d, the time spacing between potential launch times, Ti and T(i+1)
o d、 潜在发射时间Ti和T（i+1）之间的时间间隔
o n, a count of potential measurement instants
o n、 潜在测量瞬间的计数
o q, a launch probability
o q、 发射概率
o F, a selection function defining unambiguously the two packets from the stream selected for the metric
o F、 一个选择函数，明确定义为度量选择的流中的两个数据包
o P, the specification of the packet type, over and above the source and destination address
o P、 数据包类型的说明，在源地址和目标地址之上
A decimal number in the interval [0,1]
区间[0,1]中的十进制数
The result obtained by computing the Bi-Packet-Loss-Ratio over a Type-P-One-way-Bi-Packet-Loss-Geometric-Stream sample with the metric parameters.
通过使用度量参数计算P型单向双丢包几何流样本上的双丢包率得到的结果。
Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Ratio estimates the fraction of packets lost from the geometric stream of Bi-Packet probes.
Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Ratio估计从Bi分组探测的几何流中丢失的分组的分数。
Refer to Section 4.6.
参考第4.6节。
Because Type-P-One-way-Bi-Packet-Loss-Geometric-Stream is sampled in general (when the launch probability q <1), the metrics described in this section can be regarded as statistical estimators of the corresponding idealized version corresponding to q = 1. Estimation variance as it applies to Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Loss-Ratio is described in [SBDR08].
由于P型-单向-双包丢失-几何流通常是抽样的（当发射概率q<1时），因此本节中描述的度量可以被视为对应于q=1的相应理想化版本的统计估计器。[SBDR08]中描述了适用于类型P-单向-双包丢失-几何-流丢失率的估计方差。
For other issues, refer to Section 4.7
有关其他问题，请参阅第4.7节
Refer to Section 4.8.
参考第4.8节。
Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Episode-Duration
类型-P-单向-双包-丢失-几何-流-事件-持续时间
o Src, the IP address of a source host
o Src，源主机的IP地址
o Dst, the IP address of a destination host
o Dst，目标主机的IP地址
o T0, the randomly selected starting time [RFC3432] for periodic launch opportunities
o T0，随机选择的周期性发射机会的开始时间[RFC3432]
o d, the time spacing between potential launch times, Ti and T(i+1)
o d、 潜在发射时间Ti和T（i+1）之间的时间间隔
o n, a count of potential measurement instants
o n、 潜在测量瞬间的计数
o q, a launch probability
o q、 发射概率
o F, a selection function defining unambiguously the two packets from the stream selected for the metric
o F、 一个选择函数，明确定义为度量选择的流中的两个数据包
o P, the specification of the packet type, over and above the source and destination address
o P、 数据包类型的说明，在源地址和目标地址之上
A non-negative number of seconds
非负秒数
The result obtained by computing the Bi-Packet-Loss-Episode-Duration-Number over a Type-P-One-way-Bi-Packet-Loss-Geometric-Stream sample with the metric parameters, then multiplying the result by the launch spacing parameter d.
通过使用度量参数计算P型单向双包丢失几何流样本上的双包丢失事件持续时间数，然后将结果乘以发射间隔参数d而获得的结果。
Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Episode-Duration estimates the average duration of a loss episode, measured in seconds. The duration measured in packets is obtained by dividing the metric value by the packet launch spacing parameter d.
Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-spice-Duration估计丢失事件的平均持续时间，以秒为单位。通过将度量值除以数据包启动间隔参数d来获得以数据包为单位测量的持续时间。
Refer to Section 4.6.
参考第4.6节。
Because Type-P-One-way-Bi-Packet-Loss-Geometric-Stream is sampled in general (when the launch probability q <1), the metrics described in this section can be regarded as statistical estimators of the corresponding idealized version corresponding to q = 1. Estimation variance as it applies to Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Episode-Duration is described in [SBDR08].
由于P型-单向-双包丢失-几何流通常是抽样的（当发射概率q<1时），因此本节中描述的度量可以被视为对应于q=1的相应理想化版本的统计估计器。[SBDR08]中描述了适用于类型-P-单向-双包丢失-几何-流-事件-持续时间的估计方差。
For other issues, refer to Section 4.7
有关其他问题，请参阅第4.7节
Refer to Section 4.8.
参考第4.8节。
Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Episode-Frequency
类型-P-单向-双包-丢失-几何-流-插曲-频率
o Src, the IP address of a source host
o Src，源主机的IP地址
o Dst, the IP address of a destination host
o Dst，目标主机的IP地址
o T0, the randomly selected starting time [RFC3432] for periodic launch opportunities
o T0，随机选择的周期性发射机会的开始时间[RFC3432]
o d, the time spacing between potential launch times, Ti and T(i+1)
o d、 潜在发射时间Ti和T（i+1）之间的时间间隔
o n, a count of potential measurement instants
o n、 潜在测量瞬间的计数
o q, a launch probability
o q、 发射概率
o F, a selection function defining unambiguously the two packets from the stream selected for the metric
o F、 一个选择函数，明确定义为度量选择的流中的两个数据包
o P, the specification of the packet type, over and above the source and destination address
o P、 数据包类型的说明，在源地址和目标地址之上
A positive number
正数
The result obtained by computing the Bi-Packet-Loss-Episode-Frequency-Number over a Type-P-One-way-Bi-Packet-Loss-Geometric-Stream sample with the metric parameters, then dividing the result by the launch spacing parameter d.
通过使用度量参数计算P型单向双包丢失几何流样本上的双包丢失事件频率数，然后将结果除以发射间隔参数d得到的结果。
Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Episode-Frequency estimates the average frequency per unit time with which loss episodes start (or finish). The frequency relative to the count of potential probe launches is obtained by multiplying the metric value by the packet launch spacing parameter d.
Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-spice-Frequency估计每单位时间内丢失事件开始（或结束）的平均频率。通过将度量值乘以分组发射间隔参数d，获得与潜在探头发射计数相关的频率。
Refer to Section 4.6.
参考第4.6节。
Because Type-P-One-way-Bi-Packet-Loss-Geometric-Stream is sampled in general (when the launch probability q <1), the metrics described in this section can be regarded as statistical estimators of the corresponding idealized version corresponding to q = 1. Estimation variance as it applies to Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Episode-Frequency is described in [SBDR08].
由于P型-单向-双包丢失-几何流通常是抽样的（当发射概率q<1时），因此本节中描述的度量可以被视为对应于q=1的相应理想化版本的统计估计器。[SBDR08]中描述了适用于类型P-单向-双包丢失-几何-流-插曲-频率的估计方差。
For other issues, refer to Section 4.7
有关其他问题，请参阅第4.7节
Refer to Section 4.8.
参考第4.8节。
The general Gilbert-Elliot model is a discrete time Markov chain over two states, Good (g) and Bad (b), each with its own independent packet loss ratio. In the simplest case, the Good loss ratio is 0, while the Bad loss ratio is 1. Correspondingly, there are two independent parameters, the Markov transition probabilities P(g|b) = 1- P(b|b) and P(b|g) = 1- P(g|g), where P(i|j) is the probability to transition from state j and step n to state i at step n+1. With these parameters, the fraction of steps spent in the bad state is P(b|g)/(P(b|g) + P(g|b)), while the average duration of a sojourn in the bad state is 1/P(g|b) steps.
一般的Gilbert-Elliot模型是一个离散时间的Markov链，其状态为Good（g）和Bad（b），每个状态都有自己独立的丢包率。在最简单的情况下，良好损失率为0，而不良损失率为1。相应地，有两个独立的参数，马尔可夫转移概率P（g | b）=1-P（b | b）和P（b | g）=1-P（g | g），其中P（i | j）是在步骤n+1从状态j和步骤n转移到状态i的概率。使用这些参数，在坏状态下花费的步数分数为P（b | g）/（P（b | g）+P（g | b）），而在坏状态下逗留的平均持续时间为1/P（g | b）步数。
Now identify the steps of the Markov chain with the possible sending times of packets for a Type-P-One-way-Bi-Packet-Loss-Geometric-Stream with launch spacing d. Suppose the loss episode metrics Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Ratio and Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Episode-Duration take the values r and m, respectively. Then, from the discussion in Section 6.1.5, the following can be equated:
现在，确定马尔可夫链的步骤，以及发射间隔为d的P-单向双包丢失-几何流的包的可能发送时间。假设损失事件度量Type-P-One-way-Bi-Packet-loss-Geometric-Stream-Ratio和Type-P-One-way-Bi-Packet-loss-Geometric-Stream-eposion-Duration分别取值r和m。然后，根据第6.1.5节中的讨论，可以等同于以下内容：
r = P(b|g)/(P(b|g) + P(g|b)) and m/d = 1/P(g|b).
r=P（b | g）/（P（b | g）+P（g | b））和m/d=1/P（g | b）。
These relationships can be inverted in order to recover the Gilbert model parameters:
为了恢复吉尔伯特模型参数，可以颠倒这些关系：
P(g|b) = d/m and P(b|g)=d/m/(1/r - 1)
P(g|b) = d/m and P(b|g)=d/m/(1/r - 1)
Conducting Internet measurements raises both security and privacy concerns. This memo does not specify an implementation of the metrics, so it does not directly affect the security of the Internet or of applications that run on the Internet. However,implementations of these metrics must be mindful of security and privacy concerns.
进行互联网测量会引起安全和隐私问题。此备忘录未指定指标的实现，因此它不会直接影响Internet或在Internet上运行的应用程序的安全性。然而，这些指标的实现必须考虑安全和隐私问题。
There are two types of security concerns: potential harm caused by the measurements and potential harm to the measurements. The measurements could cause harm because they are active and inject packets into the network. The measurement parameters MUST be carefully selected so that the measurements inject trivial amounts of additional traffic into the networks they measure. If they inject "too much" traffic, they can skew the results of the measurement and, in extreme cases, cause congestion and denial of service. The measurements themselves could be harmed by routers giving measurement traffic a different priority than "normal" traffic, or by an attacker injecting artificial measurement traffic. If routers can recognize measurement traffic and treat it separately, the measurements may not reflect actual user traffic. If an attacker injects artificial traffic that is accepted as legitimate, the loss rate will be artificially lowered. Therefore, the measurement methodologies SHOULD include appropriate techniques to reduce the probability that measurement traffic can be distinguished from "normal" traffic. Authentication techniques, such as digital signatures, may be used where appropriate to guard against injected traffic attacks. The privacy concerns of network measurement are limited by the active measurements described in this memo: they involve no release of user data.
有两种类型的安全问题：由测量引起的潜在危害和对测量的潜在危害。这些测量可能会造成危害，因为它们处于活动状态，并将数据包注入网络。必须仔细选择测量参数，以便测量将少量的额外流量注入到它们测量的网络中。如果它们注入了“太多”的流量，它们可能会扭曲测量结果，在极端情况下，会导致拥塞和拒绝服务。路由器赋予测量流量不同于“正常”流量的优先级，或者攻击者注入人工测量流量，可能会损害测量本身。如果路由器能够识别测量流量并单独处理，那么测量可能无法反映实际的用户流量。如果攻击者注入被认为合法的人工流量，则损失率将被人为降低。因此，测量方法应包括适当的技术，以降低测量流量可与“正常”流量区分的概率。在适当的情况下，可以使用诸如数字签名之类的认证技术来防止注入流量攻击。网络测量的隐私问题受到本备忘录中所述主动测量的限制：它们不涉及用户数据的发布。
[RFC2680] Almes, G., Kalidindi, S., and M. Zekauskas, "A One-way Packet Loss Metric for IPPM", RFC 2680, September 1999.
[RFC2680]Almes，G.，Kalidini，S.，和M.Zekauskas，“IPPM的单向数据包丢失度量”，RFC 2680，1999年9月。
[RFC3393] Demichelis, C. and P. Chimento, "IP Packet Delay Variation Metric for IP Performance Metrics (IPPM)", RFC 3393, November 2002.
[RFC3393]Demichelis，C.和P.Chimento，“IP性能度量的IP数据包延迟变化度量（IPPM）”，RFC 3393，2002年11月。
[RFC3611] Friedman, T., Caceres, R., and A. Clark, "RTP Control Protocol Extended Reports (RTCP XR)", RFC 3611, November 2003.
[RFC3611]Friedman，T.，Caceres，R.，和A.Clark，“RTP控制协议扩展报告（RTCP XR）”，RFC 36112003年11月。
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate Requirement Levels", BCP 14, RFC 2119, March 1997.
[RFC2119]Bradner，S.，“RFC中用于表示需求水平的关键词”，BCP 14，RFC 2119，1997年3月。
[RFC3432] Raisanen, V., Grotefeld, G., and A. Morton, "Network performance measurement with periodic streams", RFC 3432, November 2002.
[RFC3432]Raisanen，V.，Grotefeld，G.，和A.Morton，“周期流的网络性能测量”，RFC 3432，2002年11月。
[RFC2330] Paxson, V., Almes, G., Mahdavi, J., and M. Mathis, "Framework for IP Performance Metrics", RFC 2330, May 1998.
[RFC2330]Paxson，V.，Almes，G.，Mahdavi，J.，和M.Mathis，“IP性能度量框架”，RFC 2330，1998年5月。
[RFC3357] Koodli, R. and R. Ravikanth, "One-way Loss Pattern Sample Metrics", RFC 3357, August 2002.
[RFC3357]Koodli，R.和R.Ravikanth，“单向损失模式样本度量”，RFC 3357，2002年8月。
[SBDR08] IEEE/ACM Transactions on Networking, 16(2): 307-320, "A Geometric Approach to Improving Active Packet Loss Measurement", 2008.
[SBDR08]IEEE/ACM网络事务，16（2）：307-320，“改进主动分组丢失测量的几何方法”，2008年。
[Gilbert] Gilbert, E.N., "Capacity of a Burst-Noise Channel. Bell System Technical Journal 39 pp 1253-1265", 1960.
[Gilbert]Gilbert，E.N.，“突发噪声信道的容量。贝尔系统技术期刊39页1253-1265”，1960年。
[Elliot] Elliott, E.O., "Estimates of Error Rates for Codes on Burst-Noise Channels. Bell System Technical Journal 42 pp 1977-1997", 1963.
[Elliot]Elliott，E.O.，“突发噪声信道上代码错误率的估计。贝尔系统技术期刊42页1977-1997”，1963年。
Authors' Addresses
作者地址
Nick Duffield AT&T Labs-Research 180 Park Avenue Florham Park, NJ 07932 USA
美国新泽西州弗洛勒姆公园公园大道180号尼克·达菲尔德AT&T实验室研究中心，邮编：07932
Phone: +1 973 360 8726
Fax: +1 973 360 8871
EMail: duffield@research.att.com
URI: http://www.research.att.com/people/Duffield_Nicholas_G
Phone: +1 973 360 8726
Fax: +1 973 360 8871
EMail: duffield@research.att.com
URI: http://www.research.att.com/people/Duffield_Nicholas_G
Al Morton AT&T Labs 200 Laurel Avenue South Middletown,, NJ 07748 USA
美国新泽西州劳雷尔大道南米德尔顿200号阿尔莫顿AT&T实验室，邮编：07748
Phone: +1 732 420 1571
Fax: +1 732 368 1192
EMail: acmorton@att.com
URI: http://home.comcast.net/~acmacm/
Phone: +1 732 420 1571
Fax: +1 732 368 1192
EMail: acmorton@att.com
URI: http://home.comcast.net/~acmacm/
Joel Sommers Colgate University 304 McGregory Hall Hamilton, NY 13346 USA
Joel Sommers高露洁大学304 McGregory Hall Hamilton，NY 13346美国
Phone: +1 315 228 7587
Fax:
EMail: jsommers@colgate.edu
URI: http://cs.colgate.edu/faculty/jsommers
Phone: +1 315 228 7587
Fax:
EMail: jsommers@colgate.edu
URI: http://cs.colgate.edu/faculty/jsommers