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(See the Legal Provisions document at https://trustee.ietf.org/license-info for more information.) -- The document date (March 4, 2007) is 6257 days in the past. Is this intentional? Checking references for intended status: Informational ---------------------------------------------------------------------------- == Unused Reference: 'I-D.ietf-ippm-multimetrics' is defined on line 623, but no explicit reference was found in the text == Outdated reference: A later version (-12) exists of draft-ietf-ippm-multimetrics-02 Summary: 1 error (**), 0 flaws (~~), 3 warnings (==), 7 comments (--). Run idnits with the --verbose option for more detailed information about the items above. -------------------------------------------------------------------------------- 2 Network Working Group A. Morton, Ed. 3 Internet-Draft AT&T Labs 4 Intended status: Informational S. Van den Berghe, Ed. 5 Expires: September 5, 2007 Ghent University - IBBT 6 March 4, 2007 8 Framework for Metric Composition 9 draft-ietf-ippm-framework-compagg-03 11 Status of this Memo 13 By submitting this Internet-Draft, each author represents that any 14 applicable patent or other IPR claims of which he or she is aware 15 have been or will be disclosed, and any of which he or she becomes 16 aware will be disclosed, in accordance with Section 6 of BCP 79. 18 Internet-Drafts are working documents of the Internet Engineering 19 Task Force (IETF), its areas, and its working groups. Note that 20 other groups may also distribute working documents as Internet- 21 Drafts. 23 Internet-Drafts are draft documents valid for a maximum of six months 24 and may be updated, replaced, or obsoleted by other documents at any 25 time. It is inappropriate to use Internet-Drafts as reference 26 material or to cite them other than as "work in progress." 28 The list of current Internet-Drafts can be accessed at 29 http://www.ietf.org/ietf/1id-abstracts.txt. 31 The list of Internet-Draft Shadow Directories can be accessed at 32 http://www.ietf.org/shadow.html. 34 This Internet-Draft will expire on September 5, 2007. 36 Copyright Notice 38 Copyright (C) The IETF Trust (2007). 40 Abstract 42 This memo describes a framework for composing and aggregating metrics 43 (both in time and in space) defined by RFC 2330 and developed by the 44 IPPM working group. The framework describes the generic composition 45 and aggregation mechanisms. It provides a basis for additional 46 documents that implement this framework for detailed, and practically 47 useful, compositions and aggregations of metrics. 49 Requirements Language 51 The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", 52 "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this 53 document are to be interpreted as described in RFC 2119 [RFC2119]. 55 Table of Contents 57 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 3 58 1.1. Motivation . . . . . . . . . . . . . . . . . . . . . . . . 3 59 1.1.1. Reducing Measurement Overhead . . . . . . . . . . . . 3 60 1.1.2. Measurement Re-use . . . . . . . . . . . . . . . . . . 4 61 1.1.3. Data Reduction and Consolidation . . . . . . . . . . . 4 62 1.1.4. Implications on Measurement Design and Reporting . . . 5 63 2. Purpose and Scope . . . . . . . . . . . . . . . . . . . . . . 5 64 3. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 5 65 3.1. Measurement Point . . . . . . . . . . . . . . . . . . . . 5 66 3.2. Complete path . . . . . . . . . . . . . . . . . . . . . . 6 67 3.3. Complete path metric . . . . . . . . . . . . . . . . . . . 6 68 3.4. Composed Metric . . . . . . . . . . . . . . . . . . . . . 6 69 3.5. Composition Function . . . . . . . . . . . . . . . . . . . 6 70 3.6. Ground Truth . . . . . . . . . . . . . . . . . . . . . . . 6 71 3.7. Sub-interval . . . . . . . . . . . . . . . . . . . . . . . 6 72 3.8. Sub-path . . . . . . . . . . . . . . . . . . . . . . . . . 6 73 3.9. Sub-path metrics . . . . . . . . . . . . . . . . . . . . . 6 74 4. Description of Metric Types . . . . . . . . . . . . . . . . . 7 75 4.1. Temporal Aggregation Description . . . . . . . . . . . . . 7 76 4.2. Spatial Aggregation Description . . . . . . . . . . . . . 7 77 4.3. Spatial Composition Description . . . . . . . . . . . . . 8 78 4.4. Help Metrics . . . . . . . . . . . . . . . . . . . . . . . 8 79 4.5. Higher Order Composition . . . . . . . . . . . . . . . . . 9 80 5. Requirements for Composed Metrics . . . . . . . . . . . . . . 9 81 6. Guidelines for Defining Composed Metrics . . . . . . . . . . . 10 82 6.1. Ground Truth: Comparison with other IPPM Metrics . . . . . 10 83 6.1.1. Ground Truth for Temporal Aggregation . . . . . . . . 12 84 6.1.2. Ground Truth for Spatial Aggregation . . . . . . . . . 13 85 6.2. Deviation from the Ground Truth . . . . . . . . . . . . . 13 86 6.3. Incomplete Information . . . . . . . . . . . . . . . . . . 13 87 7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 13 88 8. Security Considerations . . . . . . . . . . . . . . . . . . . 14 89 9. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . 14 90 10. References . . . . . . . . . . . . . . . . . . . . . . . . . . 14 91 10.1. Normative References . . . . . . . . . . . . . . . . . . . 14 92 10.2. Informative References . . . . . . . . . . . . . . . . . . 14 93 Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 14 94 Intellectual Property and Copyright Statements . . . . . . . . . . 16 96 1. Introduction 98 The IPPM framework [RFC2330] describes two forms of metric 99 composition, spatial and temporal. Also, the text suggests that the 100 concepts of the analytical framework (or A-frame) would help to 101 develop useful relationships to derive the composed metrics from real 102 metrics. The effectiveness of composed metrics is dependent on their 103 usefulness in analysis and applicability to practical measurement 104 circumstances. 106 This memo expands on the notion of composition, and provides a 107 detailed framework for several classes of metrics that were mentioned 108 in the original IPPM framework. The classes include temporal 109 aggregation, spatial aggregation, and spatial composition. 111 1.1. Motivation 113 Network operators have deployed measurement systems to serve many 114 purposes, including performance monitoring, maintenance support, 115 network engineering, and customer reporting. The collection of 116 elementary measurements alone is not enough to understand a network's 117 behaviour. In general, measurements need to be post-processed to 118 present the most relevant information for each purpose. The first 119 step is often a process of "composition" of single measurements or 120 measurement sets into other forms. Composition and aggregation 121 present several more post-processing opportunities to the network 122 operator, and we describe the key motivations below. 124 1.1.1. Reducing Measurement Overhead 126 A network's measurement possibilities scale upward with the square of 127 the number of nodes. But each measurement implies overhead, in terms 128 of the storage for the results, the traffic on the network (assuming 129 active methods), and the OA&M for the measurement system itself. In 130 a large network, it is impossible to perform measurements from each 131 node to all others. 133 An individual network operator should be able to organize their 134 measurement paths along the lines of physical topology, or routing 135 areas/Autonomous Systems, and thus minimize dependencies and overlap 136 between different measurement paths. This way, the sheer number of 137 measurements can be reduced, as long as the operator has a set of 138 methods to estimate performance between any particular nodes when 139 needed. 141 Composition and aggregation play a key role when the path of interest 142 spans multiple networks, and where each operator conducts their own 143 measurements. Here, the complete path performance may be estimated 144 from measurements on the component parts. 146 Operators that take advantage of the composition and aggregation 147 methods recognize that the estimates may exhibit some additional 148 error beyond that inherent in the measurements themselves, and so 149 they are making a trade-off to achieve reasonable measurement system 150 overhead. 152 1.1.2. Measurement Re-use 154 There are many different measurement users, each bringing specific 155 requirements for the reporting timescale. Network managers and 156 maintenance forces prefer to see results presented very rapidly, to 157 detect problems quickly or see if their action has corrected a 158 problem. On the other hand, network capacity planners and even 159 network users sometimes prefer a long-term view of performance, for 160 example to check trends. How can one set of measurements serve both 161 needs? 163 The answer lies in temporal aggregation, where the short-term 164 measurements needed by the operations community are combined to 165 estimate a longer-term result for others. Also, problems with the 166 measurement system itself may be isolated to one or more of the 167 short-term measurements, rather than possibly invalidating an entire 168 long-term measurement if the problem was undetected. 170 1.1.3. Data Reduction and Consolidation 172 Another motivation is data reduction. Assume there is a network 173 domain in which delay measurements are performed among a subset of 174 its nodes. A network manager might ask whether there is a problem 175 with the network delay in general. It would be desirable to obtain a 176 single value that gives an indication of the overall network delay. 177 Spatial aggregation methods would address this need, and can produce 178 the desired "single figure of merit" asked for, one that may also be 179 useful in trend analysis. 181 The overall value would be calculated from the elementary delay 182 measurements, but it not obvious how: for example, it may not to be 183 reasonable to average all delay measurements, as some paths (e.g. 184 having a higher bandwidth or more important customers) might be 185 considered more critical than others. 187 Metric composition can help to provide, from raw measurement data, 188 some tangible, well-understood and agreed upon information about the 189 service guarantees provided by a network. Such information can be 190 used in the Service Level Agreement/Service Level Specification (SLA/ 191 SLS) contracts between a service provider and its customers. 193 1.1.4. Implications on Measurement Design and Reporting 195 If a network measurement system operator anticipates needing to 196 produce overall metrics by composition, then it is prudent to keep 197 that requirement in mind when considering the measurement design and 198 sampling plan. Also, certain summary statistics are more conducive 199 to composition than others, and this figures prominently in the 200 design of measurements and when reporting the results. 202 2. Purpose and Scope 204 The purpose of this memo is provide a common framework for the 205 various classes of metrics based on composition of primary metrics. 206 The scope is limited to the definitions of metrics that are composed 207 from primary metrics using a deterministic function. Key information 208 about each metric, such as its assumptions under which the 209 relationship holds, and possible sources of error/circumstances where 210 the composition may fail, are included. 212 At this time, the scope of effort is limited to the metrics for 213 packet loss, delay, and delay variation. Composition of packet 214 reordering metrics is considered a research topic, and beyond the 215 scope at the time this memo was prepared. 217 This memo will retain the terminology of the IPPM Framework 218 [RFC2330]as much as possible, but will extend the terminology when 219 necessary. It is assumed that the reader is familiar with the 220 concepts introduced in [RFC2330], as they will not be repeated here. 222 3. Terminology 224 This section defines the terminology applicable to the processes of 225 Metric Composition and Aggregation. 227 3.1. Measurement Point 229 The logical or physical location where packet observations are made. 230 The term Measurement Point is synonymous with the term "observation 231 position" used in [RFC2330] when describing the notion of wire time. 232 A measurement point may be at the boundary between a host and an 233 adjacent link (physical), or it may be within a host (logical) that 234 performs measurements where the difference between host time and wire 235 time is understood. 237 3.2. Complete path 239 The complete path is the true path that a packet would follow as it 240 traverses from the packet's Source to its Destination. 242 3.3. Complete path metric 244 The complete path metric is the Source to Destination metric that a 245 composed metric is estimating. A complete path metric represents the 246 ground-truth for a composed metric. 248 3.4. Composed Metric 250 A composed metric is an estimate of an actual metric describing the 251 performance of a path over some time interval. A composed metric is 252 derived from other metrics by applying a deterministic process or 253 function (e.g., a composition function). 255 3.5. Composition Function 257 A composition function is a deterministic process applied to 258 individual metrics to derive another metric (such as a Composed 259 metric). 261 3.6. Ground Truth 263 As applied here, the notion of ground truth is defined as the actual 264 performance of a network path over some time interval. The ground 265 truth is metric based on the (unavailable) measurement that a 266 composed metric seeks to estimate. 268 3.7. Sub-interval 270 A Sub-interval is a time interval that is included in another 271 interval. 273 3.8. Sub-path 275 A Sub-path is a portion of the complete path where at least the Sub- 276 path Source and Destination hosts are constituents of the complete 277 path. We say that this sub-path is "involved" in the complete path. 279 3.9. Sub-path metrics 281 A sub-path path metric is an element of the process to derive a 282 Composite metric, quantifying some aspect of the performance a 283 particular sub-path from its Source to Destination. 285 4. Description of Metric Types 287 This section defines the various classes of Composition. There are 288 two classes more accurately described as aggregation over time and 289 space, and the third involves concatenation in space. 291 4.1. Temporal Aggregation Description 293 Aggregation in time is defined as the composition of metrics with the 294 same type and scope obtained in different time instants or time 295 windows. For example, starting from a time series of the 296 measurements of maximum and minimum One-Way Delay on a certain 297 network path obtained over 5-minute intervals, we obtain a time 298 series measurement with a coarser resolution (60 minutes) by taking 299 the max of 12 consecutive 5-minute maxima and the min of 12 300 consecutive 5-minute minima. 302 The main reason for doing time aggregation is to reduce the amount of 303 data that has to be stored, and make the visualization/spotting of 304 regular cycles and/or growing or decreasing trends easier. Another 305 useful application is to detect anomalies or abnormal changes in the 306 network characteristics. 308 In RFC 2330, the term "temporal composition" is introduced and 309 differs from temporal aggregation in that it refers to methodologies 310 to predict future metrics on the basis of past observations, 311 exploiting the time correlation that certain metrics can exhibit. We 312 do not consider this type of composition here. 314 >>>>>>>>Comment: Why no forecasting? This was apparently a limit on 315 the Geant2 project, but may not apply here. 317 4.2. Spatial Aggregation Description 319 Aggregation in space is defined as the combination of metrics of the 320 same type and different scope, in order to estimate the overall 321 performance of a larger domain. This combination may involve 322 weighing the contributions of the input metrics. 324 Suppose we want to compose the average One-Way-Delay (OWD) 325 experienced by flows traversing all the Origin-Destination (OD) pairs 326 of a network domain (where the inputs are already metric 327 "statistics"). Since we wish to include the effect of the traffic 328 matrix on the result, it makes sense to weight each metric according 329 to the traffic carried on the corresponding OD pair: 331 OWD_sum=f1*OWD_1+f2*OWD_2+...+fn*OWD_n 332 where fi=load_OD_i/total_load. 334 A simple average OWD across all network OD pairs would not use the 335 traffic weighting. 337 Another example metric that is "aggregated in space", is the maximum 338 edge-to-edge delay across a single domain. Assume that a Service 339 Provider wants to advertise the maximum delay that transit traffic 340 will experience while passing through his/her domain. There can be 341 multiple edge-to-edge paths across a domain, and the Service Provider 342 chooses either to publish a list of delays (each corresponding to a 343 specific edge-to-edge path), or publish a single maximum value. The 344 latter approach simplifies the publication of measurement 345 information, and may be sufficient for some purposes. Similar 346 operations can be provided to other metrics, e.g. "maximum edge-to- 347 edge packet loss", etc. 349 We suggest that space aggregation is generally useful to obtain a 350 summary view of the behaviour of large network portions, or in 351 general of coarser aggregates. The metric collection time instant, 352 i.e. the metric collection time window of measured metrics is not 353 considered in space aggregation. We assume that either it is 354 consistent for all the composed metrics, e.g. compose a set of 355 average delays all referred to the same time window, or the time 356 window of each composed metric does not affect aggregated metric. 358 4.3. Spatial Composition Description 360 Concatenation in space is defined as the composition of metrics of 361 same type and (ideally) different spatial scope, so that the 362 resulting metric is representative of what the metric would be if 363 obtained with a direct measurement over the sequence of the several 364 spatial scopes. An example is the sum of OWDs of different edge-to- 365 edge domain's delays, where the intermediate edge points are close to 366 each other or happen to be the same. In this way, we can for example 367 estimate OWD_AC starting from the knowledge of OWD_AB and OWD_BC. 368 Note that there may be small gaps in measurement coverage, likewise 369 there may be small overlaps (e.g., the link where test equipment 370 connects to the network). 372 One key difference from examples of aggregation in space is that all 373 sub-paths contribute equally to the composed metric, independent of 374 the traffic load present. 376 4.4. Help Metrics 378 Finally, note that in practice there is often the need of extracting 379 a new metric making some computation over one or more metrics with 380 the same spatial and time scope. For example, the composed metric 381 rtt_sample_variance may be composed from two different metrics: the 382 help metric rtt_square_sum and the statistical metric rtt_sum. This 383 operation is however more a simple calculation and not an aggregation 384 or a concatenation, and we'll not investigate it further in this 385 memo. 387 4.5. Higher Order Composition 389 Composed metrics might themselves be subject to further steps of 390 composition or aggregation. An example would be a the delay of a 391 maximal domain obtained through the spatial composition of several 392 composed end-to-end delays (obtained through spatial composition). 393 All requirements for first order composition metrics apply to higher 394 order composition. 396 >>>>> Comment Response: are more examples needed here? 398 5. Requirements for Composed Metrics 400 The definitions for all composed metrics MUST include sections to 401 treat the following topics. 403 The description of each metric will clearly state: 405 1. the definition (and statistic, where appropriate); 407 2. the composition or aggregation relationship; 409 3. the specific conjecture on which the relationship is based; 411 4. a justification of practical utility or usefulness for analysis 412 using the A-frame concepts; 414 5. one or more examples of how the conjecture could be incorrect and 415 lead to inaccuracy; 417 6. the information to be reported. 419 Each metric will require a relationship to determine the aggregated 420 or composed metric. The relationships may involve conjecture, and 421 [RFC2330] lists four points that the metric definitions should 422 include: 424 o the specific conjecture applied to the metric, 425 o a justification of the practical utility of the composition, in 426 terms of making accurate measurements of the metric on the path, 428 o a justification of the usefulness of the aggregation or 429 composition in terms of making analysis of the path using A-frame 430 concepts more effective, and 432 o an analysis of how the conjecture could be incorrect. 434 For each metric, the applicable circumstances are defined, in terms 435 of whether the composition or aggregation: 437 o Requires homogeneity of measurement methodologies, or can allow a 438 degree of flexibility (e.g., active or passive methods produce the 439 "same" metric). Also, the applicable sending streams will be 440 specified, such as Poisson, Periodic, or both. 442 o Needs information or access that will only be available within an 443 operator's domain, or is applicable to Inter-domain composition. 445 o Requires precisely synchronized measurement time intervals in all 446 component metrics, or loosely synchronized, or no timing 447 requirements. 449 o Requires assumption of component metric independence w.r.t. the 450 metric being defined/composed, or other assumptions. 452 o Has known sources of inaccuracy/error, and identifies the sources. 454 6. Guidelines for Defining Composed Metrics 456 6.1. Ground Truth: Comparison with other IPPM Metrics 458 Figure 1 illustrates the process to derive a metric using spatial 459 composition, and compares the composed metric to other IPPM metrics. 461 Metrics describe the performance of sub-paths between 462 the Source and Destination of interest during time interval . 463 These metrics are the inputs for a Composition Function that produces 464 a Composed Metric. 466 Sub-Path Metrics 467 ++ M1 ++ ++ M2 ++ ++ M3 ++ 468 Src ||.......|| ||.......|| ||.......|| Dst 469 ++ `. ++ ++ | ++ ++ .' ++ 470 `. | .-' 471 `-. | .' 472 `._..|.._.' 473 ,-' `-. 474 ,' `. 475 | Composition | 476 \ Function ' 477 `._ _,' 478 `--.....--' 479 | 480 ++ | ++ 481 Src ||...............................|| Dst 482 ++ Composed Metric ++ 484 ++ Complete Path Metric ++ 485 Src ||...............................|| Dst 486 ++ ++ 487 Spatial Metric 488 ++ S1 ++ S2 ++ S3 ++ 489 Src ||........||.........||..........|| Dst 490 ++ ++ ++ ++ 492 Figure 1: Comparison with other IPPM metrics 494 The Composed Metric is an estimate of an actual metric collected over 495 the complete Source to Destination path. We say that the Complete 496 Path Metric represents the "Ground Truth" for the Composed Metric. 497 In other words, Composed Metrics seek to minimize error w.r.t. the 498 Complete Path Metric. 500 Further, we observe that a Spatial Metric I-D.ietf-ippm-multimetrics 501 [I-D.ietf-ippm-multimetrics]collected for packets traveling over the 502 same set of sub-paths provide a basis for the Ground Truth of the 503 individual Sub-Path metrics. We note that mathematical operations 504 may be necessary to isolate the performance of each sub-path. 506 Next, we consider multiparty metrics as defined in [I-D.ietf-ippm- 507 multimetrics], and their spatial composition. Measurements to each 508 of the Receivers produce an element of the one-to-group metric. 509 These elements can be composed from sub-path metrics and the composed 510 metrics can be combined to create a composed one-to-group metric. 511 Figure 2 illustrates this process. 513 Sub-Path Metrics 514 ++ M1 ++ ++ M2 ++ ++ M3 ++ 515 Src ||.......|| ||.......|| ||.......||Rcvr1 516 ++ ++ ++`. ++ ++ ++ 517 `-. 518 M4`.++ ++ M5 ++ 519 || ||.......||Rcvr2 520 ++ ++`. ++ 521 `-. 522 M6`.++ 523 ||Rcvr3 524 ++ 526 One-to-Group Metric 527 ++ ++ ++ ++ 528 Src ||........||.........||..........||Rcvr1 529 ++ ++. ++ ++ 530 `-. 531 `-. ++ ++ 532 `-||..........||Rcvr2 533 ++. ++ 534 `-. 535 `-. ++ 536 `-.||Rcvr3 537 ++ 539 Figure 2: Composition of One-to-Group Metrics 541 Here, Sub-path Metrics M1, M2, and M3 are combined using a 542 relationship to compose the metric applicable to the Src-Rcvr1 path. 543 Similarly, M1, M4, and M5 are used to compose the Src-Rcvr2 metric 544 and M1, M4, and M6 compose the Src-Rcvr3 metric. 546 The Composed One-to-Group Metric would list the Src-Rcvr metrics for 547 each Receiver in the Group: 549 (Composed-Rcvr1, Composed-Rcvr2, Composed-Rcvr3) 551 The "Ground Truth" for this composed metric is of course an actual 552 One-to-Group metric, where a single source packet has been measured 553 after traversing the Complete Paths to the various receivers. 555 6.1.1. Ground Truth for Temporal Aggregation 557 Temporal Aggregation involves measurements made over sub-intervals of 558 the desired test interval between the same Source and Destination. 559 Therefore, the "Ground Truth" is the metric measured over the desired 560 interval. 562 6.1.2. Ground Truth for Spatial Aggregation 564 Spatial Aggregation combines many measurements using a weighting 565 function to provide the same emphasis as though the measurements were 566 based on actual traffic, with inherent weights. Therefore, the 567 "Ground Truth" is the metric measured on the actual traffic instead 568 of the active streams that sample the performance. 570 6.2. Deviation from the Ground Truth 572 A metric composition can deviate from the ground truth for several 573 reasons. Two main aspects are: 575 o The propagation of the inaccuracies of the underlying measurements 576 when composing the metric. As part of the composition function, 577 errors of measurements might propagate. Where possible, this 578 analysis should be made and included with the description of each 579 metric. 581 o A difference in scope. When concatenating hop-by-hop active 582 measurement results to obtain the end-to-end metric, the actual 583 measured path will not be identical to the end-to-end path. It is 584 in general difficult to quantify this deviation, but a metric 585 definition might identify guidelines for keeping the deviation as 586 small as possible. 588 The description of the metric composition MUST include an section 589 identifying the deviation from the ground truth. 591 6.3. Incomplete Information 593 In practice, when measurements cannot be initiated on a sub-path or 594 during a particular measurement interval (and perhaps the measurement 595 system gives up during the test interval), then there will not be a 596 value for the subpath reported, and the result SHOULD be recorded as 597 "undefined". 599 7. IANA Considerations 601 This document makes no request of IANA. 603 Note to RFC Editor: this section may be removed on publication as an 604 RFC. 606 8. Security Considerations 608 The security considerations that apply to any active measurement of 609 live networks are relevant here as well. See [RFC4656]. 611 9. Acknowledgements 613 The authors would like to thank Maurizio Molina, Andy Van Maele, 614 Andreas Haneman, Igor Velimirovic, Andreas Solberg, Athanassios 615 Liakopulos, David Schitz, Nicolas Simar and the Geant2 Project. We 616 also acknowledge comments and suggestions from Phil Chimento, Emile 617 Stephan, Lei Liang, and Stephen Wolff. 619 10. References 621 10.1. Normative References 623 [I-D.ietf-ippm-multimetrics] 624 Stephan, E., "IP Performance Metrics (IPPM) for spatial 625 and multicast", draft-ietf-ippm-multimetrics-02 (work in 626 progress), October 2006. 628 [RFC2119] Bradner, S., "Key words for use in RFCs to Indicate 629 Requirement Levels", BCP 14, RFC 2119, March 1997. 631 [RFC2330] Paxson, V., Almes, G., Mahdavi, J., and M. Mathis, 632 "Framework for IP Performance Metrics", RFC 2330, 633 May 1998. 635 [RFC4656] Shalunov, S., Teitelbaum, B., Karp, A., Boote, J., and M. 636 Zekauskas, "A One-way Active Measurement Protocol 637 (OWAMP)", RFC 4656, September 2006. 639 10.2. Informative References 640 Authors' Addresses 642 Al Morton (editor) 643 AT&T Labs 644 200 Laurel Avenue South 645 Middletown,, NJ 07748 646 USA 648 Phone: +1 732 420 1571 649 Fax: +1 732 368 1192 650 Email: acmorton@att.com 651 URI: http://home.comcast.net/~acmacm/ 653 Steven Van den Berghe (editor) 654 Ghent University - IBBT 655 G. Crommenlaan 8 bus 201 656 Gent 9050 657 Belgium 659 Phone: +32 9 331 49 73 660 Email: steven.vandenberghe@intec.ugent.be 661 URI: http://www.ibcn.intec.ugent.be 663 Full Copyright Statement 665 Copyright (C) The IETF Trust (2007). 667 This document is subject to the rights, licenses and restrictions 668 contained in BCP 78, and except as set forth therein, the authors 669 retain all their rights. 671 This document and the information contained herein are provided on an 672 "AS IS" basis and THE CONTRIBUTOR, THE ORGANIZATION HE/SHE REPRESENTS 673 OR IS SPONSORED BY (IF ANY), THE INTERNET SOCIETY, THE IETF TRUST AND 674 THE INTERNET ENGINEERING TASK FORCE DISCLAIM ALL WARRANTIES, EXPRESS 675 OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTY THAT THE USE OF 676 THE INFORMATION HEREIN WILL NOT INFRINGE ANY RIGHTS OR ANY IMPLIED 677 WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. 679 Intellectual Property 681 The IETF takes no position regarding the validity or scope of any 682 Intellectual Property Rights or other rights that might be claimed to 683 pertain to the implementation or use of the technology described in 684 this document or the extent to which any license under such rights 685 might or might not be available; nor does it represent that it has 686 made any independent effort to identify any such rights. Information 687 on the procedures with respect to rights in RFC documents can be 688 found in BCP 78 and BCP 79. 690 Copies of IPR disclosures made to the IETF Secretariat and any 691 assurances of licenses to be made available, or the result of an 692 attempt made to obtain a general license or permission for the use of 693 such proprietary rights by implementers or users of this 694 specification can be obtained from the IETF on-line IPR repository at 695 http://www.ietf.org/ipr. 697 The IETF invites any interested party to bring to its attention any 698 copyrights, patents or patent applications, or other proprietary 699 rights that may cover technology that may be required to implement 700 this standard. Please address the information to the IETF at 701 ietf-ipr@ietf.org. 703 Acknowledgment 705 Funding for the RFC Editor function is provided by the IETF 706 Administrative Support Activity (IASA).