--- 1/draft-ietf-ippm-loss-pattern-04.txt 2006-02-04 23:45:35.000000000 +0100 +++ 2/draft-ietf-ippm-loss-pattern-05.txt 2006-02-04 23:45:35.000000000 +0100 @@ -1,18 +1,18 @@ IP Performance Metrics (IPPM) WG Rajeev Koodli INTERNET DRAFT Nokia Research Center -21 November 2000 R. Ravikanth +20 July 2001 R. Ravikanth Axiowave One-way Loss Pattern Sample Metrics - + 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. @@ -82,21 +82,21 @@ - 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 +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. 3. Basic Definitions: 3.1. Bursty loss: @@ -108,25 +108,23 @@ 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 to be consecutive +numbers. However, these sequence numbers must be consecutive integers. -Typo in last sentence. - 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 @@ -286,77 +284,89 @@ 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 -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). +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, , 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 , 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, , in the metric Type-P-One-Way-Loss-Period-Stream which have first entry equal to "loss period." -Thus, this statistic represents the number of packets lost in each -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. 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 , 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 +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. +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, @@ -405,21 +416,21 @@ [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, January 1997 + 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.