IP Performance Metrics (IPPM) WG Rajeev Koodli INTERNET DRAFT Nokia Research Center 20 July 2001 R. Ravikanth Axiowave One-way Loss Pattern Sample Metrics <draft-ietf-ippm-loss-pattern-05.txt> STATUS OF THIS MEMO This document is an Internet-Draft and is in full conformance with all provisions of Section 10 of RFC2026. Internet-Drafts are working documents of the Internet Engineering Task Force (IETF), its areas, and its working groups. Note that other groups may also distribute working documents as Internet- Drafts. Internet-Drafts are draft documents valid for a maximum of six months and may be updated, replaced, or obsoleted by other documents at any time. It is inappropriate to use Internet-Drafts as reference material or to cite them other than as "work in progress." The list of current Internet-Drafts can be accessed at http://www.ietf.org/ietf/1id-abstracts.txt The list of Internet-Draft shadow directories can be accessed at http://www.ietf.org/shadow.html This memo provides information for the Internet community. This memo does not specify an Internet standard of any kind. Distribution of this memo is unlimited. Abstract 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. Currently, the focus has been on specifying base metrics such as delay, loss and connectivity under the framework described in [frame-work]. It is useful to capture specific Internet behaviors under the umbrella of IPPM framework, specifying new concepts while reusing existing guidelines as much as possible. This draft proposes the use of "derived metrics" to accomplish this, specifically providing means for capturing the loss pattern on the Internet. 1. Introduction In certain real-time applications (such as packet voice and video), R. Koodli, R. Ravikanth [Page 1]

Internet-Draft Loss Pattern Sample Metrics July 2001 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. There is ample evidence in the literature indicating the importance and existence of loss burstiness and its effect on packet voice and video applications [Bolot], [Borella], [Handley], [Yajnik]. 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. The Approach This document closely follows the guidelines specified in [frame-work]. Specifically, the concepts of "singleton, sample, statistic", measurement principles, Type-P packets, as well as standard-formed packets all apply. However, since the draft proposes to capture specific Internet behaviors, modifications to the sampling process may be needed. Indeed, this is mentioned in [AKZ], where it is noted that alternate sampling procedures may be useful depending on specific circumstances. This draft 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 - 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. Otherwise, the metrics would have to be fundamentally different) - 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 [frame-work], this translates to deriving sample metrics from the respective singletons. The process of deriving sample metrics from the singletons is specified in [frame-work], [AKZ], and others. In the following sections, we apply this approach to a particular Internet behavior, namely the packet loss process. R. Koodli, R. Ravikanth [Page 2]

Internet-Draft Loss Pattern Sample Metrics July 2001 3. Basic Definitions: 3.1. Bursty loss: The loss involving consecutive packets of a stream. 3.2. Loss Distance: The difference in sequence numbers of two successively lost packets which may or may not be separated by successfully received packets. Example. Let packet with sequence number 50 be considered lost immediately after packet with sequence number 20 was considered lost. The loss distance is 30. Note that this definition does not specify exactly how to associate sequence numbers with test packets. In other words, from a timeseries sample of test packets, one may derive the sequence numbers. However, these sequence numbers must be consecutive integers. 3.3. 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 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. 4. Definitions for Samples of One-way Loss Distance, and One-way Loss Period. 4.1 Metric Name: 4.1.1 Type-P-One-Way-Loss-Distance-Stream 4.1.2 Type-P-One-Way-Loss-Period-Stream R. Koodli, R. Ravikanth [Page 3]

Internet-Draft Loss Pattern Sample Metrics July 2001 4.2 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 in reciprocal of seconds + Path, the path from Src to Dst (See [AKZ] for comments) 4.3 Metric Units 4.3.1 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 [AKZ], and loss distance is either zero or a positive integer. 4.3.2 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 [AKZ], and loss period an integer. 4.4. Definitions: 4.4.1 Type-P-One-Way-Loss-Distance-Stream When a packet is considered lost (using the definition in [AKZ]), we look at its sequence number and compare it with that of the previously lost packet. The difference is the loss distance between the lost packet and the previously lost packet. The sample would consist of <loss distance, loss> pairs. This definition assumes that sequence numbers of successive test packets increase monotonically by one. The loss distance associated with the very first packet loss is considered to be zero. The sequence number of a test packet can be derived from the timeseries sample collected by performing the loss measurement according to the methodology in [AKZ]. For example, if a loss sample consists of {<T0,0>, <T1,0>, <T2,1>, <T3,0>, <T4,0>}, the sequence numbers of the five test packets sent at T0, T1, T2, T3, and T4 can be 0, 1, 2, 3 and 4 respectively, or 100, 101, 102, 103 and 104 respectively, etc. 4.4.2 Type-P-One-Way-Loss-Period-Stream R. Koodli, R. Ravikanth [Page 4]

Internet-Draft Loss Pattern Sample Metrics July 2001 We start a counter 'n' at an initial value of zero. This counter is incremented by one each time a lost packet satisfies the Definition 3.3. The metric is defined as <loss period, loss> where "loss" is derived from the sequence of <time, loss> in Type-P-One-Way-Loss-Stream [AKZ], and loss period is set to zero when "loss" is zero in Type-P-One-Way-Loss-Stream, and loss period is set to 'n' (above) when "loss" is one in Type-P-One-Way-Loss-Stream. Essentially, when a packet is lost, the current value of "n" indicates the loss period to which this packet belongs. For a packet that is received successfully, the loss period is defined to be zero. 4.4.3 Example: Let the following set of pairs represent a Type-P-One-Way-Loss-Stream. {<T1,0>,<T2,1>,<T3,0>,<T4,0>,<T5,1>,<T6,0>,<T7,1>,<T8,0>,<T9,1>, <T10,1>} where T1, T2,..,T10 are in increasing order. Packets sent at T2, T5, T7, T9, T10 are lost. The two derived metrics can be obtained from this sample as follows. (i) Type-P-One-Way-Loss-Distance-Stream: Since packet 2 is the first lost packet, the associated loss distance is zero. For the next lost packet (packet 5), loss distance is 5-2 or 3. Similarly, for the remaining lost packets (packets 7, 9, and 10) their loss distances are 2, 2, and 1 respectively. Therefore, the Type-P-One-Way-Loss-Distance-Stream is: {<0,0>,<0,1>,<0,0>,<0,0>,<3,1>,<0,0>,<2,1>,<0,0>,<2,1>,<1,1>} (ii) The Type-P-One-Way-Loss-Period-Stream: The packet 2 sets the counter 'n' to 1, which is incremented by one for packets 5, 7 and 9 according to Definition 3.3. However, for packet 10, the counter remains at 4 satisfying Definition 3.3 again. Thus, the Type-P-One-Way-Loss-Period-Stream is: {<0,0>,<1,1>,<0,0>,<0,0>,<2,1>,<0,0>,<3,1>,<0,0>,<4,1>,<4,1>} 4.5. Methodologies: The same methodology outlined in [AKZ] can be used to conduct the sample experiments. R. Koodli, R. Ravikanth [Page 5]

Internet-Draft Loss Pattern Sample Metrics July 2001 4.6 Discussion: The Loss-Distance-Stream metric allows one to study the separation between packet losses. This could be useful in determining a "spread factor" associated with the packet loss rate. For example, for a given packet loss rate, this metric indicates how the losses are spread. On the other hand, the Loss-Period-Stream metric allows the study of loss burstiness for each occurrence of loss. Note that a single loss period of length 'n' can account for a significant portion of the overall loss rate. Note also that it is possible to measure distance between loss bursts seprated by one or more successfully received packets: See Section 5.4, and 5.5 4.7 Sampling Considerations: The proposed metrics can be used independent of the particular sampling method used. We note that Poisson sampling may not yield appropriate values for these metrics for certain real-time applications such as voice over IP, as well as to TCP-based applications. For real-time applications, it may be more appropriate to use the ON-OFF [Sriram] model, in which an ON period starts with certain probability 'p', during which certain number of packets are transmitted with mean 'lambda-on' according to geometric distribution and an OFF period starts with probability '1-p' and lasts for a period of time based on exponential distribution with rate 'lambda-off'. For TCP-based applications, one may use the model proposed in [Padhye1]. See [Padhye2] for an application of the model. 5. Statistics: 5.1 Type-P-One-Way-Loss-Noticeable-Rate Define loss of a packet to be "noticeable" [RK97] if the distance between the lost packet and the previously lost packet is no greater than delta, a positive integer, where delta is the "loss constraint". Example. Let delta = 99. Let us assume that packet 50 is lost followed by a bursty loss of length 3 starting from packet 125. All the *four* losses are noticeable. Given a Type-P-One-Way-Loss-Distance-Stream, this statistic can be computed simply as the number of losses that violate some constraint delta, divided by the number of losses. (Alternately, it can also be defined as the number of "noticeable losses" to the number R. Koodli, R. Ravikanth [Page 6]

Internet-Draft Loss Pattern Sample Metrics July 2001 of successfully received packets). This statistic is useful when the actual distance between successive losses is important. For example, many multimedia codecs can sustain losses by "concealing" the effect of loss by making use of past history information. Their ability to do so degrades with poor history resulting from losses separated by close distances. By chosing delta based on this sensitivity, one can measure how "noticeable" a loss might be for quality purposes. The noticeable loss requires a certain "spread factor" for losses in the timeseries. In the above example where loss constraint is equal to 99, a loss rate of one percent with a spread of 100 between losses (e.g., 100, 200, 300, 400, 500 out of 500 packets) may be more desirable for some applications compared to the same loss rate with a spread that violates the loss constraint (e.g., 100, 175, 275, 290, 400: losses occuring at 175 and 290 violate delta = 99). 5.2 Type-P-One-Way-Loss-Period-Total This represents the total number of loss periods, and can be derived from the loss period metric Type-P-One-Way-Loss-Period-Stream as follows: Type-P-One-Way-Loss-Period-Total = maximum value of the first entry of the set of pairs, <loss period, loss>, representing the loss metric Type-P-One-Way-Loss-Period-Stream. Note that this statistic does not describe the duration of each loss period itself. If this statistic is large, it does not mean that the losses are more spread out than they are otherwise; one or more loss periods may include bursty losses. This statistic is generally useful in gathering first order of approximation of loss spread. 5.3 Type-P-One-Way-Loss-Period-Lengths This statistic is a sequence of pairs <loss period, length>, with the "loss period" entry ranging from 1 - Type-P-One-Way-Loss-Period-Total. Thus the total number of pairs in this statistic equals Type-P-One-Way-Loss-Period-Total. In each pair, the "length" is obtained by counting the number of pairs, <loss period, loss>, in the metric Type-P-One-Way-Loss-Period-Stream which have first entry equal to "loss period." Since this statistic represents the number of packets lost in each loss period, it is an indicator of burstiness of each loss period. In conjunction with loss-period-total statistic, this statistic is generally useful in observing which loss periods are potentially more influential than others from a quality perspective. R. Koodli, R. Ravikanth [Page 7]

Internet-Draft Loss Pattern Sample Metrics July 2001 5.4 Type-P-One-Way-Inter-Loss-Period-Lengths This statistic measures distance between successive loss periods. It takes the form of a set of pairs <loss period, inter-loss-period-length>, with the "loss period" entry ranging from 1 - Type-P-One-Way-Loss-Period-Total, and "inter-loss-period-length" is the loss distance between the last packet considered lost in "loss period" 'i-1', and the first packet considered lost in "loss period" 'i', where 'i' ranges from 2 to Type-P-One-Way-Loss-Period-Total. The "inter-loss-period-length" associated with the first "loss period" is defined to be zero. This statistic allows one to consider, for example, two loss periods each of length greater than one (implying loss burst), but separated by a distance of 2 to belong to the same loss burst if such a consideration is deemed useful. When the Inter-Loss-Period-Length between two bursty loss periods is smaller, it could affect the loss concealing ability of multimedia codecs since there is relatively smaller history. When it is larger, an application may be able to rebuild its history which could dampen the effect of an impending loss (period). 5.5 Example We continue with the same example as in Section 4.4.3. The three statistics defined above will have the following values. + Let delta = 2. In Type-P-One-Way-Loss-Distance-Stream {<0,0>,<0,1>,<0,0>,<0,0>,<3,1>,<0,0>,<2,1>,<0,0>,<2,1>,<1,1>}, there are 3 loss distances that violate the delta of 2. Thus, Type-P-One-Way-Loss-Noticeable-Rate = 3/5 ((number of noticeable losses)/(number of total losses)) + In Type-P-One-Way-Loss-Period-Stream {<0,0>,<1,1>,<0,0>,<0,0>,<2,1>,<0,0>,<3,1>,<0,0>,<4,1>,<4,1>}, the largest of the first entry in the sequence of <loss period,loss> pairs is 4. Thus, Type-P-One-Way-Loss-Period-Total = 4 + In Type-P-One-Way-Loss-Period-Stream {<0,0>,<1,1>,<0,0>,<0,0>,<2,1>,<0,0>,<3,1>,<0,0>,<4,1>,<4,1>}, the lengths of individual loss periods are 1, 1, 1 and 2 respectively. Thus, Type-P-One-Way-Loss-Period-Lengths = {<1,1>,<2,1>,<3,1>,<4,2>} R. Koodli, R. Ravikanth [Page 8]

Internet-Draft Loss Pattern Sample Metrics July 2001 + In Type-P-One-Way-Loss-Period-Stream {<0,0>,<1,1>,<0,0>,<0,0>,<2,1>,<0,0>,<3,1>,<0,0>,<4,1>,<4,1>}, the loss periods 1 and 2 are separated by 3 (5-2), loss periods 2 and 3 are separated by 2 (7-5), and 3 and 4 are separated by 2 (9-7). Thus, Type-P-One-Way-Inter-Loss-Period-Lengths = {<1,0>,<2,3>,<3,2>,<4,2>} 6. Security Considerations Since this draft proposes sample metrics based on the base loss metric defined in [AKZ], it inherits the security considerations mentioned in [AKZ]. 7. Acknowledgements Many thanks to Matt Zekauskas for the constructive feedback on the draft. Thanks to Guy Almes for encouraging the work, and Vern Paxson for the comments during the IETF meetings. Thanks to Steve Glass for making the presentation at the Oslo meeting. 8. References [AKZ] G. Almes and S. Kalindindi and M. Zekauskas, "A One-way Packet Loss Metric for IPPM", RFC 2680, September 1999 [Bolot] J.-C. Bolot and A. vega Garcia, "The case for FEC-based error control for Packet Audio in the Internet", ACM Multimedia Systems, 1997. [Borella] M. S. Borella, D. Swider, S. Uludag, and G. B. Brewster, "Internet Packet Loss: Measurement and Implications for End-to-End QoS," Proceedings, International Conference on Parallel Processing, August 1998. [Handley] M. Handley, "An examination of MBONE performance", Technical Report, USC/ISI, ISI/RR-97-450, July 1997 [RK97] R. Koodli, "Scheduling Support for Multi-tier Quality of Service in Continuous Media Applications", PhD dissertation, Electrical and Computer Engineering Department, University of Massachusetts, Amherst, MA 01003. [Padhye1] J. Padhye, V. Firoiu, J. Kurose and D. Towsley, "Modeling TCP throughput: a simple model and its empirical validation", in Proceedings of SIGCOMM'98, 1998. [Padhye2] J. Padhye, J. Kurose, D. Towsley and R. Koodli, "A TCP-friendly rate adjustment protocol for continuous media flows over best-effort networks", short paper presentation in R. Koodli, R. Ravikanth [Page 9]

Internet-Draft Loss Pattern Sample Metrics July 2001 ACM SIGMETRICS'99. Available as Umass Computer Science tech report from ftp://gaia.cs.umass.edu/pub/Padhye98-tcp-friendly-TR.ps.gz [Paxson] V. Paxson, "End-to-end Internet packet dynamics", Computer Communication review, Proceedings of ACM SIGCOMM'97 Conference, Cannes, France, September 1997, 27(4), pages 139-152, October 1997 [frame-work] V. Paxson, G. Almes, J. Mahdavi, and M. Mathis, "Framework for IP Performance Metrics", RFC 2330, May 1998. [Sriram] K. Sriram and W. Whitt, "Characterizing superposition arrival processes in packet multiplexers for voice and data", IEEE Journal on Selected Areas of Communication, September 1986, pages 833-846 [Yajnik] M. Yajnik, J. Kurose and D. Towsley, "Packet loss correlation in the MBONE multicast network", Proceedings of IEEE Global Internet, London, UK, November 1996. Author's Addresses Rajeev Koodli Nokia Research Center 313, Fairchild Drive Mountain View, CA 94043 Phone: +1 650-625-2359 Email: rajeev.koodli@nokia.com Rayadurgam Ravikanth Axiowave Networks Inc. 100 Nickerson Road Marlborough, MA- 01752 Email: rravikanth@axiowave.com