📄 rfc2330.txt
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Note that these points apply to the specifications for metrics and not, for example, to packet formats where octets will likely be used in preference/addition to bits. Finally, we note that some metrics may be defined purely in terms of other metrics; such metrics are call 'derived metrics'.6.2. Measurement Methodology For a given set of well-defined metrics, a number of distinct measurement methodologies may exist. A partial list includes: + Direct measurement of a performance metric using injected test traffic. Example: measurement of the round-trip delay of an IP packet of a given size over a given route at a given time. + Projection of a metric from lower-level measurements. Example: given accurate measurements of propagation delay and bandwidth for each step along a path, projection of the complete delay for the path for an IP packet of a given size. + Estimation of a constituent metric from a set of more aggregated measurements. Example: given accurate measurements of delay for a given one-hop path for IP packets of different sizes, estimation of propagation delay for the link of that one-hop path. + Estimation of a given metric at one time from a set of related metrics at other times. Example: given an accurate measurement of flow capacity at a past time, together with a set of accurate delay measurements for that past time and the current time, and given a model of flow dynamics, estimate the flow capacity that would be observed at the current time. This list is by no means exhaustive. The purpose is to point out the variety of measurement techniques. When a given metric is specified, a given measurement approach might be noted and discussed. That approach, however, is not formally part of the specification. A methodology for a metric should have the property that it is repeatable: if the methodology is used multiple times under identical conditions, it should result in consistent measurements. Backing off a little from the word 'identical' in the previous paragraph, we could more accurately use the word 'continuity' to describe a property of a given methodology: a methodology for a given metric exhibits continuity if, for small variations in conditions, itPaxson, et. al. Informational [Page 6]RFC 2330 Framework for IP Performance Metrics May 1998 results in small variations in the resulting measurements. Slightly more precisely, for every positive epsilon, there exists a positive delta, such that if two sets of conditions are within delta of each other, then the resulting measurements will be within epsilon of each other. At this point, this should be taken as a heuristic driving our intuition about one kind of robustness property rather than as a precise notion. A metric that has at least one methodology that exhibits continuity is said itself to exhibit continuity. Note that some metrics, such as hop-count along a path, are integer- valued and therefore cannot exhibit continuity in quite the sense given above. Note further that, in practice, it may not be practical to know (or be able to quantify) the conditions relevant to a measurement at a given time. For example, since the instantaneous load (in packets to be served) at a given router in a high-speed wide-area network can vary widely over relatively brief periods and will be very hard for an external observer to quantify, various statistics of a given metric may be more repeatable, or may better exhibit continuity. In that case those particular statistics should be specified when the metric is specified. Finally, some measurement methodologies may be 'conservative' in the sense that the act of measurement does not modify, or only slightly modifies, the value of the performance metric the methodology attempts to measure. {Comment: for example, in a wide-are high-speed network under modest load, a test using several small 'ping' packets to measure delay would likely not interfere (much) with the delay properties of that network as observed by others. The corresponding statement about tests using a large flow to measure flow capacity would likely fail.}6.3. Measurements, Uncertainties, and Errors Even the very best measurement methodologies for the very most well behaved metrics will exhibit errors. Those who develop such measurement methodologies, however, should strive to:Paxson, et. al. Informational [Page 7]RFC 2330 Framework for IP Performance Metrics May 1998 + minimize their uncertainties/errors, + understand and document the sources of uncertainty/error, and + quantify the amounts of uncertainty/error. For example, when developing a method for measuring delay, understand how any errors in your clocks introduce errors into your delay measurement, and quantify this effect as well as you can. In some cases, this will result in a requirement that a clock be at least up to a certain quality if it is to be used to make a certain measurement. As a second example, consider the timing error due to measurement overheads within the computer making the measurement, as opposed to delays due to the Internet component being measured. The former is a measurement error, while the latter reflects the metric of interest. Note that one technique that can help avoid this overhead is the use of a packet filter/sniffer, running on a separate computer that records network packets and timestamps them accurately (see the discussion of 'wire time' below). The resulting trace can then be analyzed to assess the test traffic, minimizing the effect of measurement host delays, or at least allowing those delays to be accounted for. We note that this technique may prove beneficial even if the packet filter/sniffer runs on the same machine, because such measurements generally provide 'kernel-level' timestamping as opposed to less-accurate 'application-level' timestamping. Finally, we note that derived metrics (defined above) or metrics that exhibit spatial or temporal composition (defined below) offer particular occasion for the analysis of measurement uncertainties, namely how the uncertainties propagate (conceptually) due to the derivation or composition.7. Metrics and the Analytical Framework As the Internet has evolved from the early packet-switching studies of the 1960s, the Internet engineering community has evolved a common analytical framework of concepts. This analytical framework, or A- frame, used by designers and implementers of protocols, by those involved in measurement, and by those who study computer network performance using the tools of simulation and analysis, has great advantage to our work. A major objective here is to generate network characterizations that are consistent in both analytical and practical settings, since this will maximize the chances that non- empirical network study can be better correlated with, and used to further our understanding of, real network behavior.Paxson, et. al. Informational [Page 8]RFC 2330 Framework for IP Performance Metrics May 1998 Whenever possible, therefore, we would like to develop and leverage off of the A-frame. Thus, whenever a metric to be specified is understood to be closely related to concepts within the A-frame, we will attempt to specify the metric in the A-frame's terms. In such a specification we will develop the A-frame by precisely defining the concepts needed for the metric, then leverage off of the A-frame by defining the metric in terms of those concepts. Such a metric will be called an 'analytically specified metric' or, more simply, an analytical metric. {Comment: Examples of such analytical metrics might include:propagation time of a link The time, in seconds, required by a single bit to travel from the output port on one Internet host across a single link to another Internet host.bandwidth of a link for packets of size k The capacity, in bits/second, where only those bits of the IP packet are counted, for packets of size k bytes.routeThe path, as defined in Section 5, from A to B at a given time.hop count of a route The value 'n' of the route path. } Note that we make no a priori list of just what A-frame concepts will emerge in these specifications, but we do encourage their use and urge that they be carefully specified so that, as our set of metrics develops, so will a specified set of A-frame concepts technically consistent with each other and consonant with the common understanding of those concepts within the general Internet community. These A-frame concepts will be intended to abstract from actual Internet components in such a way that: + the essential function of the component is retained, + properties of the component relevant to the metrics we aim to create are retained, + a subset of these component properties are potentially defined as analytical metrics, andPaxson, et. al. Informational [Page 9]RFC 2330 Framework for IP Performance Metrics May 1998 + those properties of actual Internet components not relevant to defining the metrics we aim to create are dropped. For example, when considering a router in the context of packet forwarding, we might model the router as a component that receives packets on an input link, queues them on a FIFO packet queue of finite size, employs tail-drop when the packet queue is full, and forwards them on an output link. The transmission speed (in bits/second) of the input and output links, the latency in the router (in seconds), and the maximum size of the packet queue (in bits) are relevant analytical metrics. In some cases, such analytical metrics used in relation to a router will be very closely related to specific metrics of the performance of Internet paths. For example, an obvious formula (L + P/B) involving the latency in the router (L), the packet size (in bits) (P), and the transmission speed of the output link (B) might closely approximate the increase in packet delay due to the insertion of a given router along a path. We stress, however, that well-chosen and well-specified A-frame concepts and their analytical metrics will support more general metric creation efforts in less obvious ways. {Comment: for example, when considering the flow capacity of a path, it may be of real value to be able to model each of the routers along the path as packet forwarders as above. Techniques for estimating the flow capacity of a path might use the maximum packet queue size as a parameter in decidedly non-obvious ways. For example, as the maximum queue size increases, so will the ability of the router to continuously move traffic along an output link despite fluctuations in traffic from an input link. Estimating this increase, however, remains a research topic.} Note that, when we specify A-frame concepts and analytical metrics, we will inevitably make simplifying assumptions. The key role of these concepts is to abstract the properties of the Internet components relevant to given metrics. Judgement is required to avoid making assumptions that bias the modeling and metric effort toward one kind of design. {Comment: for example, routers might not use tail-drop, even though tail-drop might be easier to model analytically.} Finally, note that different elements of the A-frame might well make different simplifying assumptions. For example, the abstraction of a router used to further the definition of path delay might treat the router's packet queue as a single FIFO queue, but the abstraction ofPaxson, et. al. Informational [Page 10]RFC 2330 Framework for IP Performance Metrics May 1998 a router used to further the definition of the handling of an RSVP- enabled packet might treat the router's packet queue as supporting bounded delay -- a contradictory assumption. This is not to say that we make contradictory assumptions at the same time, but that two different parts of our work might refine the simpler base concept in two divergent ways for different purposes. {Comment: in more mathematical terms, we would say that the A-frame
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