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Checking references for intended status: Proposed Standard ---------------------------------------------------------------------------- (See RFCs 3967 and 4897 for information about using normative references to lower-maturity documents in RFCs) -- Looks like a reference, but probably isn't: '0' on line 662 -- Looks like a reference, but probably isn't: '1' on line 662 ** Obsolete normative reference: RFC 2680 (Obsoleted by RFC 7680) Summary: 1 error (**), 0 flaws (~~), 3 warnings (==), 3 comments (--). Run idnits with the --verbose option for more detailed information about the items above. -------------------------------------------------------------------------------- 2 Network Working Group N. Duffield 3 Internet-Draft AT&T Labs-Research 4 Intended status: Standards Track A. Morton 5 Expires: July 4, 2011 AT&T Labs 6 J. Sommers 7 Colgate University 8 December 31, 2010 10 Loss Episode Metrics for IPPM 11 draft-ietf-ippm-loss-episode-metrics-01 13 Abstract 15 The IETF has developed a one way packet loss metric that measures the 16 loss rate on a Poisson probe stream between two hosts. However, the 17 impact of packet loss on applications is in general sensitive not 18 just to the average loss rate, but also to the way in which packet 19 losses are distributed in loss episodes (i.e., maximal sets of 20 consecutively lost probe packets). This draft defines one-way packet 21 loss episode metrics, specifically the frequency and average duration 22 of loss episodes, and a probing methodology under which the loss 23 episode metrics are to be measured. 25 Requirements Language 27 The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", 28 "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this 29 document are to be interpreted as described in RFC 2119 [RFC2119] 31 Status of this Memo 33 This Internet-Draft is submitted in full conformance with the 34 provisions of BCP 78 and BCP 79. 36 Internet-Drafts are working documents of the Internet Engineering 37 Task Force (IETF). Note that other groups may also distribute 38 working documents as Internet-Drafts. The list of current Internet- 39 Drafts is at http://datatracker.ietf.org/drafts/current/. 41 Internet-Drafts are draft documents valid for a maximum of six months 42 and may be updated, replaced, or obsoleted by other documents at any 43 time. It is inappropriate to use Internet-Drafts as reference 44 material or to cite them other than as "work in progress." 46 This Internet-Draft will expire on July 4, 2011. 48 Copyright Notice 49 Copyright (c) 2010 IETF Trust and the persons identified as the 50 document authors. All rights reserved. 52 This document is subject to BCP 78 and the IETF Trust's Legal 53 Provisions Relating to IETF Documents 54 (http://trustee.ietf.org/license-info) in effect on the date of 55 publication of this document. Please review these documents 56 carefully, as they describe your rights and restrictions with respect 57 to this document. Code Components extracted from this document must 58 include Simplified BSD License text as described in Section 4.e of 59 the Trust Legal Provisions and are provided without warranty as 60 described in the Simplified BSD License. 62 This document may contain material from IETF Documents or IETF 63 Contributions published or made publicly available before November 64 10, 2008. The person(s) controlling the copyright in some of this 65 material may not have granted the IETF Trust the right to allow 66 modifications of such material outside the IETF Standards Process. 67 Without obtaining an adequate license from the person(s) controlling 68 the copyright in such materials, this document may not be modified 69 outside the IETF Standards Process, and derivative works of it may 70 not be created outside the IETF Standards Process, except to format 71 it for publication as an RFC or to translate it into languages other 72 than English. 74 Table of Contents 76 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 5 77 1.1. Background and Motivation . . . . . . . . . . . . . . . . 5 78 1.2. Loss Episode Metrics and Bi-Packet Probes . . . . . . . . 6 79 1.3. Outline and Contents . . . . . . . . . . . . . . . . . . . 7 80 2. Singleton Definition for Type-P-One-way Bi-Packet Loss . . . . 8 81 2.1. Metric Name . . . . . . . . . . . . . . . . . . . . . . . 8 82 2.2. Metric Parameters . . . . . . . . . . . . . . . . . . . . 8 83 2.3. Metric Units . . . . . . . . . . . . . . . . . . . . . . . 8 84 2.4. Metric Definition . . . . . . . . . . . . . . . . . . . . 8 85 2.5. Discussion . . . . . . . . . . . . . . . . . . . . . . . . 9 86 2.6. Methodologies . . . . . . . . . . . . . . . . . . . . . . 9 87 2.7. Errors and Uncertainties . . . . . . . . . . . . . . . . . 9 88 2.8. Reporting the Metric . . . . . . . . . . . . . . . . . . . 9 89 3. General Definition of samples for 90 Type-P-One-way-Bi-Packet-Loss . . . . . . . . . . . . . . . . 9 91 3.1. Metric Name . . . . . . . . . . . . . . . . . . . . . . . 10 92 3.2. Metric Parameters . . . . . . . . . . . . . . . . . . . . 10 93 3.3. Metric Units . . . . . . . . . . . . . . . . . . . . . . . 10 94 3.4. Metric Definition . . . . . . . . . . . . . . . . . . . . 10 95 3.5. Discussion . . . . . . . . . . . . . . . . . . . . . . . . 10 96 3.6. Methodologies . . . . . . . . . . . . . . . . . . . . . . 10 97 3.7. Errors and Uncertainties . . . . . . . . . . . . . . . . . 11 98 3.8. Reporting the Metric . . . . . . . . . . . . . . . . . . . 11 99 4. An active probing methodology for Bi-Packet Loss . . . . . . . 11 100 4.1. Metric Name . . . . . . . . . . . . . . . . . . . . . . . 11 101 4.2. Metric Parameters . . . . . . . . . . . . . . . . . . . . 11 102 4.3. Metric Units . . . . . . . . . . . . . . . . . . . . . . . 12 103 4.4. Metric Definition . . . . . . . . . . . . . . . . . . . . 12 104 4.5. Discussion . . . . . . . . . . . . . . . . . . . . . . . . 12 105 4.6. Methodologies . . . . . . . . . . . . . . . . . . . . . . 12 106 4.7. Errors and Uncertainties . . . . . . . . . . . . . . . . . 13 107 4.8. Reporting the Metric . . . . . . . . . . . . . . . . . . . 13 108 5. Loss Epsiode Proto-Metrics . . . . . . . . . . . . . . . . . . 13 109 5.1. Loss-Pair-Counts . . . . . . . . . . . . . . . . . . . . . 13 110 5.2. Bi-Packet-Loss-Ratio . . . . . . . . . . . . . . . . . . . 14 111 5.3. Bi-Packet-Loss-Episode-Duration-Number . . . . . . . . . . 14 112 5.4. Bi-Packet-Loss-Episode-Frequency-Number . . . . . . . . . 14 113 6. Loss Episode Metrics derived from Bi-Packet Loss Probing . . . 14 114 6.1. Geometric Stream: Loss Ratio . . . . . . . . . . . . . . . 15 115 6.1.1. Metric Name . . . . . . . . . . . . . . . . . . . . . 15 116 6.1.2. Metric Parameters . . . . . . . . . . . . . . . . . . 15 117 6.1.3. Metric Units . . . . . . . . . . . . . . . . . . . . . 16 118 6.1.4. Metric Definition . . . . . . . . . . . . . . . . . . 16 119 6.1.5. Discussion . . . . . . . . . . . . . . . . . . . . . . 16 120 6.1.6. Methodologies . . . . . . . . . . . . . . . . . . . . 16 121 6.1.7. Errors and Uncertainties . . . . . . . . . . . . . . . 16 122 6.1.8. Reporting the Metric . . . . . . . . . . . . . . . . . 16 123 6.2. Geometric Steam: Loss Episode Duration . . . . . . . . . . 16 124 6.2.1. Metric Name . . . . . . . . . . . . . . . . . . . . . 16 125 6.2.2. Metric Parameters . . . . . . . . . . . . . . . . . . 16 126 6.2.3. Metric Units . . . . . . . . . . . . . . . . . . . . . 17 127 6.2.4. Metric Definition . . . . . . . . . . . . . . . . . . 17 128 6.2.5. Discussion . . . . . . . . . . . . . . . . . . . . . . 17 129 6.2.6. Methodologies . . . . . . . . . . . . . . . . . . . . 17 130 6.2.7. Errors and Uncertainties . . . . . . . . . . . . . . . 17 131 6.2.8. Reporting the Metric . . . . . . . . . . . . . . . . . 18 132 6.3. Geometric Stream: Loss Episode Frequency . . . . . . . . . 18 133 6.3.1. Metric Name . . . . . . . . . . . . . . . . . . . . . 18 134 6.3.2. Metric Parameters . . . . . . . . . . . . . . . . . . 18 135 6.3.3. Metric Units . . . . . . . . . . . . . . . . . . . . . 18 136 6.3.4. Metric Definition . . . . . . . . . . . . . . . . . . 18 137 6.3.5. Discussion . . . . . . . . . . . . . . . . . . . . . . 18 138 6.3.6. Methodologies . . . . . . . . . . . . . . . . . . . . 19 139 6.3.7. Errors and Uncertainties . . . . . . . . . . . . . . . 19 140 6.3.8. Reporting the Metric . . . . . . . . . . . . . . . . . 19 141 7. Applicability of Loss Episode Metrics . . . . . . . . . . . . 19 142 7.1. Relation to Gilbert Model . . . . . . . . . . . . . . . . 19 143 8. IPR Considerations . . . . . . . . . . . . . . . . . . . . . . 20 144 9. Security Considerations . . . . . . . . . . . . . . . . . . . 20 145 10. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 20 146 11. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . 21 147 12. References . . . . . . . . . . . . . . . . . . . . . . . . . . 21 148 12.1. Normative References . . . . . . . . . . . . . . . . . . . 21 149 12.2. Informative References . . . . . . . . . . . . . . . . . . 21 150 Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 21 152 1. Introduction 154 1.1. Background and Motivation 156 Packet loss in the Internet is a complex phenomenon due to the bursty 157 nature of traffic and congestion processes, influenced by both end- 158 users and applications, and the operation of transport protocols such 159 as TCP. For these reasons, the simplest model of packet loss--the 160 single parameter Bernoulli (independent) loss model--does not 161 represent the complexity of packet loss over periods of time. 162 Correspondingly, a single loss metric--the average packet loss ratio 163 over some period of time--arising, e.g., from a stream of Poisson 164 probes as in [RFC2680] is not sufficient to determine the effect of 165 packet loss on traffic in general. 167 Moving beyond single parameter loss models, Markovian and Markov- 168 modulated loss models involving transitions between a good and bad 169 state, each with an associated loss rate, have been proposed by 170 Gilbert and more generally by Elliot. In principle, Markovian models 171 can be formulated over state spaces involving patterns of loss of any 172 desired number of packets. However further increase in the size of 173 the state space makes such models cumbersome both for parameter 174 estimation (accuracy decreases) and prediction in practice (due to 175 computational complexity and sensitivity to parameter inaccuracy). 176 In general, the relevance and importance of particular models can 177 change in time, e.g. in response to the advent of new applications 178 and services. For this reason we are drawn to empirical metrics that 179 do not depend on a particular model for their interpretation. 181 An empirical measure of packet loss complexity, the index of 182 dispersion of counts (IDC), comprise, for each t >0, the ratio v(t) \ 183 a(t) of the variance v(t) and average a(t) of the number of losses 184 over successive measurement windows of a duration t. However, a full 185 characterization of packet loss over time requires specification of 186 the IDC for each window size t>0. 188 In the standards arena, loss pattern sample metrics are defined in 189 [RFC3357]. Following the Gilbert-Elliot model, burst metrics 190 specific for VoIP that characterize complete episodes of lost, 191 transmitted and discarded packets are defined in [RFC3611] 193 All these considerations motivate formulating empirical metrics of 194 one-way packet loss that provide the simplest generalization of the 195 successful [RFC2680] that can capture deviations from independent 196 packet loss in a robust model-independent manner, and, to define 197 efficient measurement methodologies for these metrics. 199 1.2. Loss Episode Metrics and Bi-Packet Probes 201 The losses experienced by the packet stream can be viewed as 202 occurring in loss episodes, i.e., maximal set of consecutively lost 203 packets. This memo describes one-way loss episode metrics: their 204 frequency and average duration. Although the average loss ratio can 205 be expressed in terms of these quantities, they go further in 206 characterizing the statistics of the patterns of packet loss within 207 the stream of probes. This is useful information in understanding 208 the effect of packet losses on application performance, since 209 different applications can have different sensitivities to patterns 210 of loss, being sensitive not only to the long term average loss rate, 211 but how losses are distributed in time. As an example: MPEG video 212 traffic may be sensitive to loss involving the I-frame in a group of 213 pictures, but further losses within an episode of sufficiently short 214 duration have no further impact; the damage is already done. 216 The loss episode metrics presented here represent have the following 217 useful properties: 219 1. the metrics are empirical and do not depend on an underlying 220 model; e.g., the loss process is not assumed to be Markovian. On 221 the other hand, it turns out that the metrics of this memo can be 222 related to the special case of the Gilbert Model parameters; see 223 Section 7. 225 2. the metric units can be directly compared with applications or 226 user requirements or tolerance for network loss performance, in 227 the frequency and duration of loss episodes, as well as the usual 228 packet loss ratio, which can be recovered from the loss episode 229 metrics upon dividing the average loss episode duration by the 230 loss episode frequency. 232 3. the metrics provide the smallest possible increment in complexity 233 beyond, but in the spirit of, the IPPM average packet loss ratio 234 metrics [RFC2680] i.e., moving from a single metric (average 235 packet loss ratio) to a pair of metrics (loss episode frequency 236 and average loss episode duration). 238 The draft also describes a probing methodology under which loss 239 episode metrics are to be measured. The methodology comprises 240 sending probe packets in pairs, where packets within each probe pair 241 have a fixed separation, and the time between pairs takes the form of 242 a geometric distributed number multiplied by the same separation. 243 This can be regarded a generalization of Poisson probing where the 244 probes are pairs rather than single packets as in [RFC2680], and also 245 of geometric probing described in [RFC2330]. However, it should be 246 distinguished from back to back packet pairs whose change in 247 separation on traversing a link is used to probe bandwidth. In this 248 draft, the separation between the packets in a pair is the temporal 249 resolution at which different loss episodes are to be distinguished. 250 One key feature of this methodology is its efficiency: it estimates 251 the average length of loss episodes without directly measuring the 252 complete episodes themselves. Instead, this information is encoded 253 in the observed relative frequencies of the 4 possible outcomes 254 arising from the loss or successful transmission of each of the two 255 packets of the probe pairs. This is distinct from the approach of 256 [RFC3611] that reports on directly measured episodes. 258 The metrics defined in this memo are "derived metrics", according to 259 Section 6.1 of [RFC2330] the IPPM framework. They are based on the 260 singleton loss metric defined in Section 2 of [RFC2680] . 262 1.3. Outline and Contents 264 o Section 2 defines the fundamental singleton metric for the 265 possible outcomes of a probe pair: Type-P-One-way-Bi-Packet-Loss. 267 o Section 3 defines sample sets of this metric derived from a 268 general probe stream: Type-P-One-way-Bi-Packet-Loss-Stream. 270 o Section 4 defines the prime example of the Bi-Packet-Loss-Stream 271 metrics, specifically Type-P-One-way-Bi-Packet-Loss-Geometric- 272 Stream arising from the geometric stream of packet-pair probes 273 that was described informally in Section 1. 275 o Section 5 defines Loss episode proto-metrics that summarize the 276 outcomes from a stream metrics as an intermediate step to forming 277 the loss episode metrics; they need not be reported in general. 279 o Section 6 defines the final loss episode metrics that are the 280 focus of this memo, the new metrics 282 * Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Episode- 283 Duration, the average duration, in seconds, of a loss episode 285 * Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Episode- 286 Frequency, the average frequency, per second, at which loss 287 episodes start. 289 * Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Ratio, which is 290 the average packet loss ratio metric arising from the geometric 291 stream probing methodology 293 o Section 7 details applications and relations to existing loss 294 models. 296 2. Singleton Definition for Type-P-One-way Bi-Packet Loss 298 2.1. Metric Name 300 Type-P-One-way-Bi-Packet-Loss 302 2.2. Metric Parameters 304 o Src, the IP address of a source host 306 o Dst, the IP address of a destination host 308 o T1, a sending time of the first packet 310 o T2, a sending time of the second packet, with T2>T1 312 o F, a selection function defining unambiguously the two packets 313 from the stream selected for the metric. 315 o P, the specification of the packet type, over and above the source 316 and destination addresses 318 2.3. Metric Units 320 A Loss Pair is pair (l1, l2) where each of l1 and l2 is a binary 321 value 0 or 1, where 0 signifies successful transmission of a packet 322 and 1 signifies loss. 324 The metric unit for Type-P-One-way-Bi-Packet-Loss takes is a Loss 325 Pair 327 2.4. Metric Definition 329 1. "The Type-P-One-way-Bi-Packet-Loss with parameters (Src, Dst, T1, 330 T2, F, P) is (1,1)" means that Src sent the first bit of a Type-P 331 packet to Dst at wire-time T1 and the first bit of a Type-P 332 packet to Dst a wire-time T2>T1, and that neither packet was 333 received at Dst. 335 2. The Type-P-One-way-Bi-Packet-Loss with parameters (Src, Dst, T1, 336 T2, F, P) is (1,0)" means that Src sent the first bit of a Type-P 337 packet to Dst at wire-time T1 and the first bit of a Type-P 338 packet to Dst a wire-time T2>T1, and that the first packet was 339 not received at Dst, and the second packet was received at Dst 341 3. The Type-P-One-way-Bi-Packet-Loss with parameters (Src, Dst, T1, 342 T2, F, P) is (0,1)" means that Src sent the first bit of a Type-P 343 packet to Dst at wire-time T1 and the first bit of a Type-P 344 packet to Dst a wire-time T2>T1, and that the first packet was 345 received at Dst, and the second packet was not received at Dst 347 4. The Type-P-One-way-Bi-Packet-Loss with parameters (Src, Dst, T1, 348 T2, F, P) is (0,0)" means that Src sent the first bit of a Type-P 349 packet to Dst at wire-time T1 and the first bit of a Type-P 350 packet to Dst a wire-time T2>T1, and that both packet were 351 received at Dst. 353 2.5. Discussion 355 The purpose of the selection function is to specify exactly which 356 packets are to be used for measurement. The notion is taken from 357 Section 2.5 of [RFC3393], where examples are discussed. 359 2.6. Methodologies 361 The methodologies related to the Type-P-One-way-Packet-Loss metric in 362 Section 2.6 of [RFC2680] are similar for the Type-P-One-way-Bi- 363 Packet-Loss metric described above. In particular, the methodologies 364 described in RFC 2680 apply to both packets of the pair. 366 2.7. Errors and Uncertainties 368 Sources of error for the Type-P-One-way-Packet-Loss metric in Section 369 2.7 of [RFC2680] apply to each packet of the pair for the Type-P-One- 370 way-Bi-Packet-Loss metric. 372 2.8. Reporting the Metric 374 Refer to Section 2.8 of [RFC2680]. 376 3. General Definition of samples for Type-P-One-way-Bi-Packet-Loss 378 Given the singleton metric for Type-P-One-way-Bi-Packet-Loss, we now 379 define examples of samples of singletons. The basic idea is as 380 follows. We first specify a set of times T1 < T2 <...1 583 o 0 if N(0,1) + N(1,0) + N(1,1) = 0 (no probe packets lost) 585 o Undefined if N(0,1) + N(1,0) + N(0,0) = 0 (all probe packets lost) 587 Note N(0,1) + N(1,0) is zero if there are no transitions between loss 588 and no-loss outcomes. 590 5.4. Bi-Packet-Loss-Episode-Frequency-Number 592 The Bi-Packet-Loss-Episode-Frequency-Number associated with a set of 593 n loss pairs L1,,,,Ln is defined in terms of their Loss-Pair-Counts 594 as Bi-Packet-Loss-Ratio / Bi-Packet-Loss-Episode-Duration-Number, 595 when this can be defined, specifically, it is: 597 o (N(1,0)+N(1,1)) * (N(0,1)+N(1,0)) / (2*N(1,1)+N(0,1)+N(1,0) ) / n 598 if N(0,1)+N(0,1) > 0 600 o 0 if N(0,1)+N(1,0) +N(1,1) = 0 (no probe packets lost) 602 o 1 if N(0,1) +N(1,0) +N(0,0) = 0 (all probe packets lost) 604 6. Loss Episode Metrics derived from Bi-Packet Loss Probing 606 Metrics for the time frequency and time duration of loss episodes are 607 now defined as functions of set of n loss pairs L1,....,Ln. Although 608 a loss episode is defined as a maximal set of successive lost 609 packets, the loss episode metrics are not defined directly in terms 610 of the sequential patterns of packet loss exhibited by loss pairs. 612 This is because samples, including Type-P-One-way-Bi-Packet-Loss- 613 Geometric-Stream, generally do not report all lost packets in each 614 episode. Instead, the metrics are defined as functions of the Loss- 615 Pair-Counts of the sample, for reasons that are now described. 617 Consider an idealized Type-P-One-way-Bi-Packet-Loss-Geometric-Stream 618 sample in which the launch probability q =1. It is shown in [SBDR08] 619 that the average number of packets in a loss episode of this ideal 620 sample is exactly the Bi-Packet-Loss-Episode-Duration derived from 621 its set of loss pairs. Note this computation makes no reference to 622 the position of lost packet in the sequence of probes. 624 A general Type-P-One-way-Bi-Packet-Loss-Geometric-Stream sample with 625 launch probability q < 1, independently samples, with probability q, 626 each loss pair of an idealized sample. On average, the Loss-Pair- 627 Counts (if normalized by the total number of pairs) will be the same 628 as in the idealized sample. The loss episode metrics in the general 629 case are thus estimators of those for the idealized case; the 630 statistical properties of this estimation, including a derivation of 631 the estimation variance, is provided in [SBDR08]. 633 6.1. Geometric Stream: Loss Ratio 635 6.1.1. Metric Name 637 Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Ratio 639 6.1.2. Metric Parameters 641 o Src, the IP address of a source host 643 o Dst, the IP address of a destination host 645 o T0, the randomly selected starting time [RFC3432] for periodic 646 launch opportunities 648 o d, the time spacing between potential launch times, Ti and Ti+1 650 o n, a count of potential measurement instants 652 o q, a launch probability 654 o F, a selection function defining unambiguously the two packets 655 from the stream selected for the metric. 657 o P, the specification of the packet type, over and above the source 658 and destination address 660 6.1.3. Metric Units 662 A number in the interval [0,1] 664 6.1.4. Metric Definition 666 The result obtained by computing the Bi-Packet-Loss-Ratio over a 667 Type-P-One-way-Bi-Packet-Loss-Geometric-Stream sample with the metric 668 parameters. 670 6.1.5. Discussion 672 Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Ratio estimates the 673 fraction of packets lost from the geometric stream of Bi-Packet 674 probes. 676 6.1.6. Methodologies 678 Refer to Section 4.6 680 6.1.7. Errors and Uncertainties 682 Because Type-P-One-way-Bi-Packet-Loss-Geometric-Stream is sampled in 683 general (when the launch probability q <1) the metrics described in 684 this Section can be regarded as statistical estimators of the 685 corresponding idealized version corresponding to q = 1. Estimation 686 variance as it applies to Type-P-One-way-Bi-Packet-Loss-Geometric- 687 Stream-Loss-Ratio is described in [SBDR08]. 689 For other issues refer to Section 4.7 691 6.1.8. Reporting the Metric 693 Refer to Section 4.8 695 6.2. Geometric Steam: Loss Episode Duration 697 6.2.1. Metric Name 699 Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Episode-Duration 701 6.2.2. Metric Parameters 703 o Src, the IP address of a source host 705 o Dst, the IP address of a destination host 706 o T0, the randomly selected starting time [RFC3432] for periodic 707 launch opportunities 709 o d, the time spacing between potential launch times, Ti and Ti+1 711 o n, a count of potential measurement instants 713 o q, a launch probability 715 o F, a selection function defining unambiguously the two packets 716 from the stream selected for the metric. 718 o P, the specification of the packet type, over and above the source 719 and destination address 721 6.2.3. Metric Units 723 A non-negative number of seconds. 725 6.2.4. Metric Definition 727 The result obtained by computing the Bi-Packet-Loss-Episode-Duration- 728 Number over a Type-P-One-way-Bi-Packet-Loss-Geometric-Stream sample 729 with the metric parameters, then multiplying the result by the launch 730 spacing parameter d. 732 6.2.5. Discussion 734 Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Episode-Duration 735 estimates the average duration of a loss episode, measured in 736 seconds. The duration measured in packets is obtained by dividing 737 the metric value by the packet launch spacing parameter d. 739 6.2.6. Methodologies 741 Refer to Section 4.6 743 6.2.7. Errors and Uncertainties 745 Because Type-P-One-way-Bi-Packet-Loss-Geometric-Stream is sampled in 746 general (when the launch probability q <1) the metrics described in 747 this Section can be regarded as statistical estimators of the 748 corresponding idealized version corresponding to q = 1. Estimation 749 variance as it applies to Type-P-One-way-Bi-Packet-Loss-Geometric- 750 Stream-Episode-Duration is described in [SBDR08]. 752 For other issues refer to Section 4.7 754 6.2.8. Reporting the Metric 756 Refer to Section 4.8 758 6.3. Geometric Stream: Loss Episode Frequency 760 6.3.1. Metric Name 762 Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Episode-Frequency 764 6.3.2. Metric Parameters 766 o Src, the IP address of a source host 768 o Dst, the IP address of a destination host 770 o T0, the randomly selected starting time [RFC3432] for periodic 771 launch opportunities 773 o d, the time spacing between potential launch times, Ti and Ti+1 775 o n, a count of potential measurement instants 777 o q, a launch probability 779 o F, a selection function defining unambiguously the two packets 780 from the stream selected for the metric. 782 o P, the specification of the packet type, over and above the source 783 and destination address 785 6.3.3. Metric Units 787 A positive number. 789 6.3.4. Metric Definition 791 The result obtained by computing the Bi-Packet-Loss-Episode-Frequency 792 over a Type-P-One-way-Bi-Packet-Loss-Geometric-Stream sample with the 793 metric parameters, then dividing he result by the launch spacing 794 parameter d. 796 6.3.5. Discussion 798 Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Episode-Frequency 799 estimates the average frequency per unit time with which loss 800 episodes start (or finish). The frequency relative to the count of 801 potential probe launches is obtained by multiplying the metric value 802 by the packet launch spacing parameter d. 804 6.3.6. Methodologies 806 Refer toSection 4.6 808 6.3.7. Errors and Uncertainties 810 Because Type-P-One-way-Bi-Packet-Loss-Geometric-Stream is sampled in 811 general (when the launch probability q <1) the metrics described in 812 this Section can be regarded as statistical estimators of the 813 corresponding idealized version corresponding to q = 1. Estimation 814 variance as it applies to Type-P-One-way-Bi-Packet-Loss-Geometric- 815 Stream-Episode-Frequency is described in [SBDR08]. 817 For other issues refer to Section 4.7 819 6.3.8. Reporting the Metric 821 Refer to Section 4.8 823 7. Applicability of Loss Episode Metrics 825 7.1. Relation to Gilbert Model 827 The general Gilbert-Elliot model is a discrete time Markov chain over 828 two states, Good (g) and Bad (b), each with its own independent 829 packet loss rate. In the simplest case, the Good loss rate is 0 830 while the Bad loss rate is 1. Correspondingly, there are two 831 independent parameters, the Markov transition probabilities P(g|b) = 832 1- P(b|b) and P(b|g) = 1- P(g|g), where P(i|j) is the probability to 833 transition from state j and step n to state i at step n+1. With 834 these parameters, the fraction of steps spent in the bad state is 835 P(b|g)/(P(b|g) + P(g|b)) while the average duration of a sojourn in 836 the bad state is 1/P(g|b) steps. 838 Now identify the steps of the Markov chain with the possible sending 839 times of packets for a Type-P-One-way-Bi-Packet-Loss-Geometric-Stream 840 with launch spacing d. Suppose the loss episode metrics Type-P-One- 841 way-Bi-Packet-Loss-Geometric-Stream-Ratio and ype-P-One-way-Bi- 842 Packet-Loss-Geometric-Stream-Episode-Duration take the values r and m 843 respectively. Then from the discussion in Section 6.2.5 the 844 following can be equated: 846 r = P(b|g)/(P(b|g) + P(g|b)) and m/d = 1/P(g|b). 848 These relationships can be inverted in order to recover the Gilbert 849 model parameters: 851 P(g|b) = d/m and P(b|g)=d/m/(1/r - 1) 853 8. IPR Considerations 855 IPR disclosures concerning some of the material covered in this draft 856 has been made to the IETF: see https://datatracker.ietf.org/ipr/1009/ 857 , https://datatracker.ietf.org/ipr/1010/ , and 858 https://datatracker.ietf.org/ipr/1126/ 860 9. Security Considerations 862 Conducting Internet measurements raises both security and privacy 863 concerns. This memo does not specify an implementation of the 864 metrics, so it does not directly affect the security of the Internet 865 nor of applications which run on the Internet. 866 However,implementations of these metrics must be mindful of security 867 and privacy concerns. 869 There are two types of security concerns: potential harm caused by 870 the measurements, and potential harm to the measurements. The 871 measurements could cause harm because they are active, and inject 872 packets into the network. The measurement parameters MUST be 873 carefully selected so that the measurements inject trivial amounts of 874 additional traffic into the networks they measure. If they inject 875 "too much" traffic, they can skew the results of the measurement, and 876 in extreme cases cause congestion and denial of service. The 877 measurements themselves could be harmed by routers giving measurement 878 traffic a different priority than "normal" traffic, or by an attacker 879 injecting artificial measurement traffic. If routers can recognize 880 measurement traffic and treat it separately, the measurements may not 881 reflect actual user traffic. If an attacker injects artificial 882 traffic that is accepted as legitimate, the loss rate will be 883 artificially lowered. Therefore, the measurement methodologies 884 SHOULD include appropriate techniques to reduce the probability that 885 measurement traffic can be distinguished from "normal" traffic. 886 Authentication techniques, such as digital signatures, may be used 887 where appropriate to guard against injected traffic attacks. The 888 privacy concerns of network measurement are limited by the active 889 measurements described in this memo: they involve no release of user 890 data. 892 10. IANA Considerations 893 11. Acknowledgements 895 12. References 897 12.1. Normative References 899 [RFC2119] Bradner, S., "Key words for use in RFCs to Indicate 900 Requirement Levels", BCP 14, RFC 2119, March 1997. 902 [RFC2680] Almes, G., Kalidindi, S., and M. Zekauskas, "A One-way 903 Packet Loss Metric for IPPM", RFC 2680, September 1999. 905 [RFC3393] Demichelis, C. and P. Chimento, "IP Packet Delay Variation 906 Metric for IP Performance Metrics (IPPM)", RFC 3393, 907 November 2002. 909 [RFC3432] Raisanen, V., Grotefeld, G., and A. Morton, "Network 910 performance measurement with periodic streams", RFC 3432, 911 November 2002. 913 [RFC3611] Friedman, T., Caceres, R., and A. Clark, "RTP Control 914 Protocol Extended Reports (RTCP XR)", RFC 3611, 915 November 2003. 917 12.2. Informative References 919 [RFC2330] Paxson, V., Almes, G., Mahdavi, J., and M. Mathis, 920 "Framework for IP Performance Metrics", RFC 2330, 921 May 1998. 923 [RFC3357] Koodli, R. and R. Ravikanth, "One-way Loss Pattern Sample 924 Metrics", RFC 3357, August 2002. 926 [SBDR08] IEEE/ACM Transactions on Networking, 16(2): 307-320, "A 927 Geometric Approach to Improving Active Packet Loss 928 Measurement", 2008. 930 Authors' Addresses 932 Nick Duffield 933 AT&T Labs-Research 934 180 Park Avenue 935 Florham Park, NJ 07932 936 USA 938 Phone: +1 973 360 8726 939 Fax: +1 973 360 8871 940 Email: duffield@research.att.com 941 URI: http://www.research.att.com/people/Duffield_Nicholas_G 943 Al Morton 944 AT&T Labs 945 200 Laurel Avenue South 946 Middletown,, NJ 07748 947 USA 949 Phone: +1 732 420 1571 950 Fax: +1 732 368 1192 951 Email: acmorton@att.com 952 URI: http://home.comcast.net/~acmacm/ 954 Joel Sommers 955 Colgate University 956 304 McGregory Hall 957 Hamilton, NY 13346 958 USA 960 Phone: +1 315 228 7587 961 Fax: 962 Email: jsommers@colgate.edu 963 URI: http://cs.colgate.edu/faculty/jsommers