rfc3357.txt

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Network Working Group                                          R. Koodli
Request for Comments: 3357                         Nokia Research Center
Category: Informational                                     R. Ravikanth
                                                                Axiowave
                                                             August 2002


                  One-way Loss Pattern Sample Metrics

Status of this Memo

   This memo provides information for the Internet community.  It does
   not specify an Internet standard of any kind.  Distribution of this
   memo is unlimited.

Copyright Notice

   Copyright (C) The Internet Society (2002).  All Rights Reserved.

Abstract

   Using the base loss metric defined in RFC 2680, this document defines
   two derived metrics "loss distance" and "loss period", and the
   associated statistics that together capture loss patterns experienced
   by packet streams on the Internet.  The Internet exhibits certain
   specific types of behavior (e.g., bursty packet loss) that can affect
   the performance seen by the users as well as the operators.  The loss
   pattern or loss distribution is a key parameter that determines the
   performance observed by the users for certain real-time applications
   such as packet voice and video.  For the same loss rate, two
   different loss distributions could potentially produce widely
   different perceptions of performance.



















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Table of Contents

   1. Introduction                                                     3
   2. Terminology                                                      3
   3. The Approach                                                     3
   4. Basic Definitions                                                4
   5.  Definitions for Samples of One-way Loss Distance, and One-way
        Loss Period                                                    5
       5.1. Metric Names  . . . . . . . . . . . . . . . . . . . . . .  5
             5.1.1. Type-P-One-Way-Loss-Distance-Stream . . . . . . .  5
             5.1.2. Type-P-One-Way-Loss-Period-Stream . . . . . . . .  5
       5.2. Metric Parameters . . . . . . . . . . . . . . . . . . . .  5
       5.3. Metric Units  . . . . . . . . . . . . . . . . . . . . . .  5
             5.3.1. Type-P-One-Way-Loss-Distance-Stream . . . . . . .  5
             5.3.2. Type-P-One-Way-Loss-Period-Stream . . . . . . . .  5
       5.4. Definitions . . . . . . . . . . . . . . . . . . . . . . .  6
             5.4.1. Type-P-One-Way-Loss-Distance-Stream . . . . . . .  6
             5.4.2. Type-P-One-Way-Loss-Period-Stream . . . . . . . .  6
             5.4.3. Examples  . . . . . . . . . . . . . . . . . . . .  6
       5.5. Methodologies . . . . . . . . . . . . . . . . . . . . . .  7
       5.6. Discussion  . . . . . . . . . . . . . . . . . . . . . . .  8
       5.7. Sampling Considerations . . . . . . . . . . . . . . . . .  8
       5.8. Errors and Uncertainties  . . . . . . . . . . . . . . . .  8
   6. Statistics                                                       9
       6.1. Type-P-One-Way-Loss-Noticeable-Rate . . . . . . . . . . .  9
       6.2. Type-P-One-Way-Loss-Period-Total  . . . . . . . . . . . .  9
       6.3. Type-P-One-Way-Loss-Period-Lengths  . . . . . . . . . . . 10
       6.4. Type-P-One-Way-Inter-Loss-Period-Lengths  . . . . . . . . 10
       6.5. Examples  . . . . . . . . . . . . . . . . . . . . . . . . 10
   7. Security Considerations                                         11
       7.1. Denial of Service Attacks . . . . . . . . . . . . . . . . 12
       7.2. Privacy / Confidentiality . . . . . . . . . . . . . . . . 12
       7.3. Integrity . . . . . . . . . . . . . . . . . . . . . . . . 12
   8. IANA Considerations                                             12
   9. Acknowledgements                                                12
   10. Normative References                                           12
   11. Informative References                                         13
   Authors' Addresses                                                 14
   Full Copyright Statement                                           15












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1. Introduction

   In certain real-time applications (such as packet voice and video),
   the loss pattern or loss distribution is a key parameter that
   determines the performance observed by the users.  For the same loss
   rate, two different loss distributions could potentially produce
   widely different perceptions of performance.  The impact of loss
   pattern is also extremely important for non-real-time applications
   that use an adaptive protocol such as TCP.  Refer to [4], [5], [6],
   [11] for evidence as to the importance and existence of loss
   burstiness and its effect on packet voice and video applications.

   Previously, the focus of the IPPM had been on specifying base metrics
   such as delay, loss and connectivity under the framework described in
   RFC 2330.  However, specific Internet behaviors can also be captured
   under the umbrella of the IPPM framework, specifying new concepts
   while reusing existing guidelines as much as possible.  In this
   document, we propose two derived metrics, called "loss distance" and
   "loss period", with associated statistics, to capture packet loss
   patterns.  The loss period metric captures the frequency and length
   (burstiness) of loss once it starts, and the loss distance metric
   captures the spacing between the loss periods.  It is important to
   note that these metrics are derived based on the base metric Type-P-
   One-Way-packet-Loss.

2. Terminology

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", "OPTIONAL", and
   "silently ignore" in this document are to be interpreted as described
   in BCP 14, RFC 2119 [2].

3. The Approach

   This document closely follows the guidelines specified in [3].
   Specifically, the concepts of singleton, sample, statistic,
   measurement principles, Type-P packets, as well as standard-formed
   packets all apply.  However, since the document proposes to capture
   specific Internet behaviors, modifications to the sampling process
   MAY be needed.  Indeed, this is mentioned in [1], where it is noted
   that alternate sampling procedures may be useful depending on
   specific circumstances.  This document proposes that the specific
   behaviors be captured as "derived" metrics from the base metrics the
   behaviors are related to.  The reasons for adopting this position are
   the following:






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   -  it provides consistent usage of singleton metric definition for
      different behaviors (e.g., a single definition of packet loss is
      needed for capturing burst of losses, 'm out of n' losses etc.)

   -  it allows re-use of the methodologies specified for the singleton
      metric with modifications whenever necessary

   -  it clearly separates few base metrics from many Internet behaviors

   Following the guidelines in [3], this translates to deriving sample
   metrics from the respective singletons.  The process of deriving
   sample metrics from the singletons is specified in [3], [1], and
   others.

   In the following sections, we apply this approach to a particular
   Internet behavior, namely the packet loss process.

4. Basic Definitions

   Sequence number: Consecutive packets in a time series sample are
                    given sequence numbers that are consecutive
                    integers.  This document does not specify exactly
                    how to associate sequence numbers with packets.  The
                    sequence numbers could be contained within test
                    packets themselves, or they could be derived through
                    post-processing of the sample.

   Bursty loss: The loss involving consecutive packets of a stream.

   Loss Distance: The difference in sequence numbers of two successively
                  lost packets which may or may not be separated by
                  successfully received packets.

   Example: In a packet stream, the packet with sequence number 20 is
            considered lost, followed by the packet with sequence number
            50.  The loss distance is 30.

   Loss period: Let P_i be the i'th packet.  Define f(P_i) = 1 if P_i is
                lost, 0 otherwise.  Then, a loss period begins if
                f(P_i) = 1 and f(P_(i-1)) = 0

   Example: Consider the following sequence of lost (denoted by x) and
            received (denoted by r) packets.

         r r r x r r x x x r x r r x x x






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   Then, with `i' assigned as follows,
                               1 1 1 1 1 1
   i:      0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5

   f(P_i) is,

   f(P_i): 0 0 0 1 0 0 1 1 1 0 1 0 0 1 1 1

      and there are four loss periods in the above sequence beginning at
      P_3, P_6, P_10, and P_13.

5. Definitions for Samples of One-way Loss Distance, and One-way Loss
   Period

5.1. Metric Names

5.1.1. Type-P-One-Way-Loss-Distance-Stream

5.1.2. Type-P-One-Way-Loss-Period-Stream

5.2. Metric Parameters

   Src,         the IP address of a host

   Dst,         the IP address of a host

   T0,          a time

   Tf,          a time

   lambda,      a rate of any sampling method chosen in reciprocal of
                seconds

5.3. Metric Units

5.3.1. Type-P-One-Way-Loss-Distance-Stream

   A sequence of pairs of the form <loss distance, loss>, where loss is
   derived from the sequence of <time, loss> in [1], and loss distance
   is either zero or a positive integer.

5.3.2. Type-P-One-Way-Loss-Period-Stream

   A sequence of pairs of the form <loss period, loss>, where loss is
   derived from the sequence of <time, loss> in [1], and loss period is
   an integer.





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