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INTERNET-DRAFT                                   Nick Duffield (Editor)
draft-ietf-psamp-framework-03.txt                  AT&T Labs - Research
June 2003
Expires: December 2003

                 A Framework for Passive Packet Measurement

   Copyright (C) The Internet Society (2003).  All Rights Reserved.

   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-

   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

   The list of Internet-Draft Shadow Directories can be accessed at

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   this document are to be interpreted as described in RFC 2119.


   A wide range of traffic engineering and troubleshooting tasks rely
   on timely and detailed traffic measurements that can be
   consistently interpreted. This document describes a framework for
   packet sampling that is (a) general enough to serve as the basis
   for a wide range of operational tasks, and (b) needs only a small
   set of packet selectors that facilitate ubiquitous deployment in
   router interfaces or dedicated measurement devices, even at very
   high speeds.  The framework also covers reporting and exporting
   functions used by the sampling element, and configuration of the
   sampling element.

   Comments on this document should be addressed to the PSAMP WG
   mailing list: psamp@ops.ietf.org
   To subscribe: psamp-request@ops.ietf.org, in body: subscribe
   Archive: https://ops.ietf.org/lists/psamp/

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0 Contents

   1 Motivation  .................................................  3
   2 Elements, Terminology, and Architecture  ....................  3
   3 Requirements  ...............................................  6
     3.1 Selection Process Requirements  .........................  6
     3.2 Reporting Process Requirements  .........................  6
     3.3 Export Process Requirements  ............................  7
     3.4 Configuration Requirements  .............................  7
   4 Packet Selection ............................................  8
     4.1 Packet Selection Terminology ............................  8
     4.2 Packet Selection Operations for a PSAMP .................  9
     4.3 Input Sequence Numbers for Primitive Selectors .......... 11
     4.4 Composite Selectors .  .................................. 12
     4.5 Constraints on the Sampling Frequency ................... 12
     4.6 Criteria for Choice of Selection Operations  ............ 12
   5 Reporting Process  .......................................... 13
     5.1 Mandatory Contents of Packet Reports (MUST) ............. 13
     5.2 Recommended Contents for Packet Reports (SHOULD) ........ 13
     5.3 Report Interpretation  .................................  14
   7 Parallel Measurement Processes  ............................. 15
   6 Export Process .............................................. 15
     7.1 Collector Destination  .................................. 15
     7.2 Local Export  ........................................... 15
     7.3 Reliable vs. Unreliable Transport  ...................... 16
     7.4 Limiting Delay in Exporting Measurement Packets  ........ 16
     7.5 Configurable Export Rate Limit  ......................... 16
     7.6 Congestion-aware Unreliable Transport  .................. 17
     7.7 Collector-based Rate Reconfiguration  ................... 17
       7.7.1 Changing the Export Rate and Other Rates  ........... 17
       7.7.2 Notions of Fairness  ................................ 18
       7.7.3 Behavior Under Overload and Failure  ................ 19
   8 Configuration and Management  ............................... 19
   9 Feasibility and Complexity  ................................. 20
     9.1 Feasibility  ............ ............................... 20
       9.1.1 Filtering  .......................................... 20
       9.1.2 Sampling  ........................................... 20
       9.1.3 Hashing  ............................................ 20
       9.1.4 Reporting  .......................................... 21
       9.1.5 Export  ............................................. 21
     9.2 Potential Hardware Complexity  .......................... 21
   10 Applications  .............................................. 22
     10.1 Baseline Measurement and Drill Down  ................... 22
     10.2 Passive Performance Measurement  ....................... 23
     10.3 Troubleshooting  ....................................... 23
   11 Security Considerations .................................... 24
   12 References  ................................................ 25
   13 Authors' Addresses  ........................................ 26
   14 Intellectual Property Statement  ........................... 27
   15 Full Copyright Statement  .................................. 27

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1 Motivation

   This document describes a framework in which to define a standard
   set of capabilities for network elements to sample subsets of
   packets by statistical and other methods. The framework will
   accommodate future work to (i) specify a set of selectors by which
   packets are sampled (ii) specify the information that is to be made
   available for reporting on sampled packets; (iii) describe a
   protocol by which information on sampled packets is reported to
   applications; (iv) describe a protocol by which packet selection
   and reporting are configured.

   The motivation to standardize these capabilities comes from the
   need for measurement-based support for network management and
   control across multivendor domains.  This requires domain wide
   consistency in the types of selection schemes available, the manner
   in which the resulting measurements are presented, and
   consequently, consistency of the interpretation that can be put on

   The capabilities are positioned as suppliers of packet samples to
   higher level consumers, including both remote collectors and
   applications, and on board measurement-based applications.  Indeed,
   development of the standards within the framework described here
   should be open to influence by the requirements of standards in
   related IETF WGs, for example, IP Performance Metrics (IPPM)
   [PAMM98] and Internet Traffic Engineering (TEWG) [LCTV02].
   Conversely, we expect that aspects of this framework not
   specifically concerned with the central issue of packet selection
   and report formation may be able to leverage work in other
   WGs. Potential examples are the format and export of measurement
   reports, which may leverage the information model and export
   protocols of IP Flow Information Export (IPFIX) [QZCZ03], and work
   in congestion aware unreliable transport in the Datagram Congestion
   Control Protocol (DCCP) [FHK02], and related work in The Stream
   Control Transmission Protocol (SCTP) [SCTP] and [PR-SCTP].

2 Elements, Terminology, and Architecture

   This section defines the basic elements of the PSAMP framework. At
   the highest level, the architecture comprises observation points
   (at which packets are observed), measurement processes (which
   select packets and construct reports on them) and export processes
   (which export reports to collectors). The full defintions of these
   terms now follow.

   * Observation Point: the observation point is a location in the
       network where a packet stream is observed. Examples are, a line

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       to which a probe is attached, a shared medium, such as an
       Ethernet-based LAN, a single port of a router, or set of
       interfaces (physical or logical) of a router, an embedded
       measurement subsystem within an interface.

   * Measurement Process: the combination of a selection process
       followed by a reporting process.

   * Packet Stream: a sequence of packets, each of which was observed
       at the observation point. Note that when packets are sampled
       from a stream, the selected packets usually do not have common
       properties by which they can be distinguished from packets that
       have not been selected.  Therefore we define here the term
       stream instead of flow, which is defined as set of packets with
       common properties [QuZC02].

   * Packet Content: the union of the following: packet header, packet
       payload, encapsulation headers, and link layer headers.

   * Observed Packet Stream: the packet stream comprising all packets
       observed at the observation point.

   * Selection Process: a selection process selects a substream of
       packets from the observed packet stream. A selection process
       entails the composition of one or more selectors in succession,
       acting on each packet in the observed packet stream. When
       selectors are composed, the output stream packet issuing from
       one selector forms the input packet stream for the succeeding

   * Selector (or selection operation): a configurable packet
       selection operation that acts on single packets. It takes as
       its input, the content of a single packet from a packet stream,
       information derived from the packet's treatment at the
       observation point, and selection state that may be maintained
       at the observation point.  If the packet is selected, this same
       information may be considered as the output. Selectors may
       change the selection state.

   * Composite Selector: an ordered composition of selectors.

   * Primitive Selector: a selector that is not a composition of
       multiple selectors.

   * Selection State: the selection process may maintain state
       information for use by the selection process and/or the
       reporting process. At a given time, the selection state may
       depend on packets observed up that time and/or other variables.
       Examples include sequence numbers of packets at the input of
       selectors, timestamps, iterators for pseudorandom number
       generators, calculated hash values, and indicators of whether a

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       packet was selected by a given selector.

   * Reporting Process: the creation of a report stream of information
       on packets selected by a selection processes, in preparation
       for export. The input to a reporting process comprises that
       information available to a selection process, for the selected
       packets.  The report stream contains two distinguished types of
       information: packet reports, and report interpretation.

   * Packet Reports: a configurable subset of the per packet input to
       the reporting process.

   * Report Interpretation: subsidiary information relating to one or
       more packets, that is used for interpretation of their packet
       reports. Examples include configuration parameters of the PSAMP
       device, and configuration parameters of the selection and
       reporting process.

   * Export Process: sends the output of one or more reporting process
       to one or more collectors.

   * Collector: a collector receives a report stream exported by one
       or more measurement processes. In some cases, the entity that
       hosts the measurement and/or export process may also serve as
       the collector.

   * Measurement packets: one or packet reports, and perhaps report
       interpretation, are bundled by the export process into a
       measurement packet for export to a collector.

   Various possibilities for the high level architecture of these
   elements is as follows.

    = Observation Point, MP = Measurement Process, EP = Export Process

   +---------------------+                 +------------------+
   |Observation Point(s) |                 | Collector(1)     |
   |MP(s)--->EP----------+---------------->|                  |
   |MP(s)--->EP----------+-------+-------->|                  |
   +---------------------+       |         +------------------+
   +---------------------+       |         +------------------+
   |Observation Point(s) |       +-------->| Collector(2)     |
   |MP(s)--->EP----------+---------------->|                  |
   +---------------------+                 +------------------+

   |Observation Point(s) |
   |MP(s)--->EP---+      |
   |              |      |
   |Collector(3)<-+      |

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3 Requirements

   3.1 Selection Process Requirements.

   * Ubiquity: The selectors must be simple enough to be implemented
       ubiquitously at maximal line rate.

   * Applicability: the set of selectors must be rich enough to
       support a range of existing and emerging measurement based
       applications and protocols. This requires a workable trade-off
       between the range of traffic engineering applications and
       operational tasks it enables, and the complexity of the set of

   * Extensibility: to allow for additional packet selectors to
     support future applications.

   * Flexibility: to support selection of packets using different
       network protocols or encapsulation layers (e.g. IPv4, IPv6,
       MPLS, etc), and under packet encryption.

   * Robust Selection: packet selection MUST be robust w.r.t. attempts
       to craft a packet stream from which packets are selected
       disproportionately (e.g. to evade selection, or overload the
       measurement system).

   * Parallel Measurements: multiple independent measurement
       processes at the same entity.

   * Non-contingency: in order to satisfy the ubiquity requirement,
       the selection decision for each packet MUST NOT depend on
       future packets.  Rather, the selection decision MUST be capable
       of being made on the basis of the selection process input up to
       and including the packet in question. This excludes selection
       functions that require caching of packet for selection
       contingent on subsequent packets. See also the timeliness
       requirement following.

   Selectors are outlined in Section 4, and described in more detail in
   the companion document [ZMRD03].

   3.2 Reporting Process Requirements

   * Transparency: allow transparent interpretation of measurements as
       communicated by PSAMP reporting, without any need to obtain
       additional information concerning the observed packet stream.

   * Robustness to Information Loss: allow robust interpretation of

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       measurements with respect to reports missing due to data loss,
       e.g. in transport, or within the measurement, reporting or
       exporting processes.  Inclusion in reporting of information
       that enables the accuracy of measurements to be determined.

   * Faithfulness: all reported quantities that relate to the packet
       treatment MUST reflect the router state and configuration
       encountered by the packet at the time it is received by the
       measurement process.

   * Privacy: selection of the content of packet reports will be
       cognizant of privacy and anonymity issues while being
       responsive to the needs of measurement applications, and in
       accordance with RFC 2804.  Full packet capture of arbitrary
       packet streams is explicitly out of scope.

   A specific reporting processes meeting these requirements, and the
   requirement for ubiquity, is described in Section 5.

   3.3 Export Process Requirements

   * Timeliness: reports on selected packets MUST be made available
       to the collector quickly enough to support near real time
       applications. Specifically, any report on a packet MUST be
       dispatched within 1 second of the time of receipt of the packet
       by the measurement process.

   * Congestion Avoidance: export of a report stream across a network
       MUST be congestion avoiding in compliance with RFC 2914.

   * Secure Export:

       - confidentiality: the option to encrypt exported data MUST be

       - integrity: alterations in transit to exported data MUST be
       detectable at the collector

       - authenticity: authenticity of exported data MUST be
       verifiable by the collector in order to detect forged data.

       The motivation here is the same as for security in IPFIX
       export; see Sections 6.3 and 10 of [QZCZ03].

   3.4 Configuration Requirements

   * Ease of Configuration: of sampling and export parameters,
       e.g. for automated remote reconfiguration in response to

   * Secure Configuration: the option to configure via protocols that

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       prevent unauthorized reconfiguration or eavesdropping on
       configuration communications MUST be available.  Eavesdropping
       on configuration might allow an attacker to gain knowledge that
       would be helpful in crafting a packet stream to (for example)
       evade subversion, or overload the measurement infrastructure.

   Configuration is discussed in Section 8. Feasibility and complexity
   of PSAMP operations is discussed in Section 9.

   Reuse of existing protocols will be encouraged provided the
   protocol capabilities are compatible with the requirements laid out
   in this document.

4 Packet Selection

   4.1 Packet Selection Terminology.

   * Filtering: a filter is a selection operation that selects a
       packet deterministically based on the packet content, its
       treatment, and functions of these occurring in the selection
       state. Examples include match/mask filtering, and hash-based

   * Sampling: a selection operation that is not a filter is called a
       sampling operation. This reflects the intuitive notion that if
       the selection of a packet cannot be exactly predicted from its
       content, there must be some type of sampling taking place.

   * Content-independent Sampling: a sampling operation that does not
       use packet content (or quantities derived from it) as the basis
       for selection is called a content-independent sampling
       operation. Examples include systematic sampling, and uniform
       pseudorandom sampling driven by a pseudorandom number whose
       generation is independent of packet content. Note that in
       independent sampling it is not necessary to access the packet
       content in order to make the selection decision.

   * Content-dependent Sampling: a sampling operation where selection
       is dependent on packet content is called a content-dependent
       sampling operation. Examples include pseudorandom selection
       according to a probability that depends on the contents of a
       packet field; note that this is not a filter.

   * Emulated Sampling: selection operations in any of the above four
       categories may be emulated by operations in the same or another
       category for the purposes of implementation. For example,
       uniform pseudorandom sampling may be emulated by hash-based
       selection, using suitable hash function and hash domain.

   * Hash-based selection: a filter specified by a hash domain, a hash

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       function, and hash range and a hash selection range.

   * Hash domain: a subset of the packet content and the packet
       treatment, viewed as an N-bit string for some positive integer

   * Hash range: a set of M-bit strings for some positive integer M.

   * Hash function: a deterministic map from the hash domain into the
       hash range.

   * Selection range: a subset of the hash range. The packet is
       selected if the action of the hash function on the hash domain
       for the packet yields a result in the hash selection range.

   * Pool size: the size of a set of packets in a packet stream.

   * Sample size: the size of a set of packets selected by a sampling

   * Target Sampling Frequency: a configurable sampling frequency in a
       sampling operation.

   * Attained Sampling Frequency: Given a subset of packets in a stream
       input to a sampling operation, the attained sampling frequency is
       the ratio of the sample size to the pool size.

4.2 Packet Selection Operations for a PSAMP

   A spectrum of packet selection operations is described in detail in
   [ZMRD03]. Here we only briefly summarize the meanings for

   A PSAMP selection process MUST support at least one of the
   following selectors.

   * Systematic Time Based:
        packet selection is triggered at periodic instants separated
        by a time called the Spacing. All packets that arrive within a
        certain time of the trigger (called the Interval Length) are

   * Systematic Count Based:
        similar to systematic time based expect that selection is
        reckoned w.r.t. packet count rather than time. Packet
        selection is triggered periodically by packet count, a number
        of successive packets being selected subsequent to each trigger.

   * Uniform Probabilistic: packets are selected independently with
        fixed sampling probability p.

   * Non-uniform Probabilistic:

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        packets are selected independently with probability p that
        depends on packet content.

   * Probabilistic n-out-of-N:
        form each count-based successive block of N packets, n are
        selected at random

   * Match/Mask Filtering:

        This entails taking the masking portions of the packet
        (i.e. taking the bitwise AND with a binary mask) and selecting
        the packet if the result falls in a specified range.  This
        specification doesn't preclude the future definition of a high
        level syntax for defining filtering in a concise way (e.g. TCP
        port taking a particular value) providing that syntax can be
        compiled into the bitwise expression.

        Match/mask operations SHOULD be available for different
        protocol portions of the packet:

        o the IP header (excluding options in IPv4, stacked headers in

        o transport header

        o encapsulation headers (including MPLS label stack, ATOM)

        When an entity offers Match/Mask filtering in the selection
        process and, in its usual capacity other than in performing
        PSAMP functions, identifies or processes information from one
        or more of the above protocols, then the information SHOULD be
        made available for filtering. For example, when an entity
        routes based on destination IP address, that field should be
        made available.  Conversely, an entity that does not route is
        not expected to be able to locate an IP address within a
        packet, or make it available for filtering, although it MAY do

   * Hash-based Selection:
        Hash-based selection will employ one or more hash functions to
        be standardized.  The hash domain is specified by a bitmaps on
        the IP packet header and the IP payload.

        When the hash function is sufficiently good, hash-based
        selection can be used to emulate uniform random sampling over
        the hash domain. The target sampling frequency is then the
        ratio of the size of the selection range to the hash range.

        Applications of hash-based selection include:

        o Trajectory Sampling: all routers use the same hash selector;

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          the hash domain includes only portions of the packet that do
          not change from hope to hop (e.f. TTL is excluded). Hence
          packets are consistently selected in the sense that they
          are selected at all routers on their path or none. Reports
          also include a second hash (the label hash) that
          distinguishes different packets. Reports of a given packet
          reaching the collector from different routers can be used to
          reconstruct the path taken by the packet. Trajectory
          Sampling is proposed in [DuGr01]; further description is
          found in [ZMRD03]; some applications are described in
          Section 10.

        o Consistent Flow Sampling: the hash domain is a flow key. For
          a given flow, either all or none of its packets are
          sampled. This is accomplished without the need to maintain
          flow state.

        Some applications need to calculate packet hashes for purposes
        other than selection (e.g. the label hash in Trajectory
        Sampling). This can be achieved by placing a calculated hash
        in the selection state, and setting the selection range to be
        the whole of the hash range.

   * Router State Filtering:
        This class of filters selects a packet on based on the following
        conditions, combined with the AND, OR or NOT operators:

        o Ingress interface at which packet arrives equals a specified
        o Egress interface to which packet is routed to equals a
        specified value
        o Origin AS equals a specified value or lies within a given
        o Destination AS equals a specified value or lies within a given
        o Packet violated acl on the router
        o Failed rpf
        o Failed rsvp
        o No route found for the packet

        Router architectural considerations may preclude some
        information concerning the packet treatment, e.g routing
        state, being available at line rate for selection of
        packets. However, if selection not based on routing state has
        reduced down from line rate, subselection based on routing
        state may be feasible.

   4.3 Input Sequence Numbers for Primitive Selectors.

   Each instance of a primitive selector MUST maintain a count of
   packets presented at its input. The counter value is to be included

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   as a sequence number for selected packets. This enables
   applications to determine the attained frequency at which packets
   are selected, and hence correctly normalize network usage estimates
   regardless of loss of information, whether this occurs because of
   discard of packet reports in the measurement or reporting process
   (e.g. due to resource contention), or loss of measurement packets
   in transmission or collection; see [PPM01].  The sequence numbers
   are considered as part of the packet's selection state.

   4.4 Composite Selectors

   The ability to compose selectors in a selection process SHOULD be
   provided. The following combinations appear to be most useful for

   * filtering followed by sampling
   * sampling followed by filtering

   Composite selectors are useful for drill down applications. The
   first component of a composite selector can be used to reduce the
   load on the second component. In this setting, the advantage to be
   gained from a given ordering can depend on the composition of the
   packet stream.

   4.5 Constraints on the Sampling Frequency

   Sampling at full line rate, i.e. with probability 1, is not
   excluded in principle, although resource constraints may not
   support it in practice.

   4.6 Criteria for Choice of Selection Operations

   In current practice, sampling has been performed using particular
   algorithms, including:

          - pseudorandom independent sampling with probability 1/N;
          - systematic sampling of every Nth packet.

   The question arises as to whether both of these should be
   standardized as distinct selection operations, or whether they can
   be regarded as different implementations of a single selection

   To determine the answer to this question, we need to consider

      (a) measured or assumed statistical properties of the packet
      stream, e.g., one or more of the following:
          - contents of different packets are statistically independent
          - correlations between contents of different packets decay
            at a specified rate
          - contents of certain fields within the same packet are

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            significantly variable and exhibit small cross correlation
      (b) the desired reference sampling model, e.g., one of:
          - sample packets with long term probability 1/N
          - sample packets independent with probability 1/N
      (c) the set of possible alternatives and implementations, e.g.,
      one of:
          - pseudorandom independent sampling with probability 1/N
          - systematic sampling with period N
          - hash-based sampling with target probability 1/N
      (d) the tolerance for error in the applications that use the

   We can say that a given alternative from (c) reproduces a reference
   model (b) for the applications if the results obtained using them
   are sufficiently accurate in (d) for traffic satisfying an assumed
   statistical properties in (a). Clearly, application to evaluate
   methods in (c) requires developing agreement on the relevant
   properties in (a), (b) and (d).

   Example: systematic sampling with period N will not count the
   occurrence of closely space packets (less than N counts apart) from
   the same flow. Thus for applications that are concerned with the
   joint statistics of multiple packets within flows, systematic
   sampling may not reproduce the results obtained with random
   sampling sufficiently accurately.

5 Reporting Process

   5.1 Mandatory Contents of Packet Reports (MUST)

   The reporting process MUST include the following in each packet report:

       (i) the input sequence number(s) of any sampling operation
       that acted on the packet in the instance of a measurement
       process of which the reporting process is a component.

   The reporting process MUST be able to include the following
   in each packet report, as a configurable option:

       (ii) some number of contiguous bytes from the start of the

   Some devices may not have the resource capacity or functionality to
   provide more detailed reports that those in (i) and (ii)
   above. Using this minimum required reporting functionality, the
   reporting process places the burden of interpretation on the collector,
   or on applications that it supplies.

   5.2 Recommended Contents for Packet Reports (SHOULD)

   The reporting process SHOULD provide for the inclusion in packet

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   reports of the following information, inclusion any or all being
   configurable as a option.

        (iii) fields relating to the following protocols
        used in the packet, specifically: IPv4, IPV6, transport
        protocols, MPLS, ATOM.

        (iv) packet treatment, including:

        - identifiers for any input and output interfaces of the
        observation point that were traversed by the packet

        - source and destination AS

        (v) selection state associated with the packet, including:

        - timestamps

        - hashes, where calculated.

   The specific fields will include those set out as requirements for
   IPFIX [QZCZ03], with modifications appropriate to reporting on
   single packets rather than flows.

   When an entity that hosts a reporting process and, in its usual
   capacity other than performing PSAMP functions, identifies or
   process one or more of the above fields, then the contents of each
   such field(s) SHOULD be made available for optional reporting. For
   example, when a device routes based on destination IP address, that
   field should be made available.  Conversely, an entity that does
   not route is not expected to be able to locate an IP address within
   a packet, or make it available for reporting, although it MAY do

   5.3 Report Interpretation

   Information for use in report interpretation MUST include (i)
   configuration parameters of the selectors of the packets reported
   on; (ii) format of the packet reports (iii) configuration
   parameters and state information of the network element; (iv)
   indication of the inherent accuracy of the reported quantities,
   e.g., of timestamps; (v) identifiers for observation point,
   measurement process, and export process.

   The requirements for robustness and transparency are motivations
   for including report interpretation in the report stream. Inclusion
   makes the report stream self-defining.  The PSAMP framework
   excludes reliance on an alternative model in which interpretation
   is recovered out of band. This latter approach is not robust with
   respect to undocumented changes in selector configuration, and may
   give rise to future architectural problems for network management

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   systems to coherently manage both configuration and data collection.

   It is not envisaged that all report interpretation be included
   in every packet report. Many of the quantities listed above are
   expected to be relatively static; they could be communicated
   periodically, and upon change.

   To conserve network bandwidth and resources at the collector, the
   measurement packets may be compressed before export.  Compression
   is expected to be quite effective since the sampled packets may
   share many fields in common, e.g. if a filter focuses on packets
   with certain values in particular header fields. Using compression,
   however, could impact the timeliness of reports. Any consequent
   delay MUST not violate the timeliness requirement for availability
   of packet reports at the collector.

6  Parallel Measurement Processes

   Because of the increasing number of distinct measurement
   applications, with varying requirements, it is desirable to set up
   parallel measurement processes on a stream of packets.  A PSAMP
   device SHOULD support more than one independently configurable
   measurement process. The measurement process may have an exclusive
   export process, or may share it with other measurement processes.

   Each of the parallel measurement processes SHOULD be
   independent. However, resource constraints may prevent complete
   reporting on a packet selected by multiple selection processes. In
   this case, reporting for the packet MUST be complete for at least
   one measurement process; other measurement processes need only
   report that they selected the packet. The priority amongst
   measurement processes to report packets MUST be configurable.

   It is not proposed to standardize the number of parallel
   measurement processes.

7 Export Process

   7.1 Collector Destination

   When exporting to a remote collector, the collector is identified
   by IP address and port number.

   7.2 Local Export

   The report stream may be directly exported to on-board measurement
   based applications, for example those that form composite
   statistics from more than one packet. Local export may be presented
   through an interface direct to the higher level applications, i.e.,
   through an API, rather than employing the transport used for
   off-board export.

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   A possible example of local export could be that packets selected
   by the PSAMP measurement process serve as the input for the IPFIX
   protocol, which then forms flow records out of the stream of
   selected packets. Note that IPFIX being still developed; this is
   given only as a possible example.

   7.3  Reliable vs. Unreliable Transport

   The export of the report stream does not require reliable
   export. On the contrary, retransmission of lost measurement packets
   consumes additional network resources and requires maintenance of
   state by the export process. As such, the export process would have
   to be able to receive and process acknowledgments, and to store
   unacknowledged data. Furthermore, the entity that hosts the export
   process may not possess its own network address (for example an
   embedded measurement subsystem in an interface) at which to receive
   acknowledgments. These requirements would be a significant
   impediment to having ubiquitous support PSAMP.

   Instead, it is proposed that the export process support unreliable
   export.  Sequence numbers on the measurement packets would indicate
   when loss has occurred, and the analysis of the collected
   measurement data can account for this loss.  In some sense, packet
   loss becomes another form of sampling (albeit a less desirable, and
   less controlled, form of sampling).

   7.4 Limiting Delay in Exporting Measurement Packets

   The export process may queue the report stream in order to export
   multiple reports in a single measurement packet. Any consequent
   delay MUST still allow for timely availability of packet reports
   at the collector.

   7.5 Configurable Export Rate Limit

   The export process MUST be able to limit its export rate; otherwise
   it could overload the network and/or the collector. Note this
   problem would be exacerbated if using reliable transport mode,
   since any lost packets would be retransmitted, thereby imposing an
   additional load on the network.

   At times, the reporting process may generate new reports or report
   interpretation faster than the allowed export rate.  In this
   situation, the export process MUST discard the excess reports
   rather than transmitting them to the collector. Sequence numbers
   reported for selector input enable correction for lost reports. An
   additional sequence number for dispatched measurement packets
   enables the collector to determine the degree of loss in

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   There are two options for a configurable rate limit. First, if the
   transport protocol has a configurable rate limit, that can be used.
   The second option is to limit the rate at which measurement packets
   are supplied to the transport protocol. A candidate for
   implementation of rate limiting is the leaky bucket, with tokens
   corresponding e.g. to bytes or packets.

   The export rate limit MUST be configurable per export process. Note
   that since congestion loss can occur at any link on the export
   path, it is not sufficient to limit rate simply as a function of
   the bandwidth of the interface out of which export takes place.

   7.6 Congestion-aware Unreliable Transport

   Exported measurement traffic competes for resources with other
   Internet transfers.  Congestion-aware export is important to ensure
   that the measurement packets do not overwhelm the capacity of the
   network or unduly degrade the performance of other applications,
   while making good use of available bandwidth resources.

   Choice of transport for PSAMP has to be made under the following

   (i) IESG has mandated that all transport in new protocols must be
     congestion aware
   (ii) reliable transport is too onerous for general entities that
     support PSAMP (see Section 7.3)
   (iii) there currently exists no IETF standardized unreliable
     congestion-aware transport

   In the absence of an existing IETF standardized unreliable
   congestion-aware protocol, PSAMP will provisionally nominate the
   reliable congestion aware transport protocol TCP as the interim
   transport protocol for export. From the preceding arguments, TCP
   is unsatisfactory for final standardization in PSAMP. In the
   meantime, the PSAMP WG will evaluate (at least) the following
   alternatives for congestion aware unreliable transport, as they
   become available, with a view to selecting one of them and
   discarding TCP:

   (i) unreliable transport protocols adopted in the future by the

   (ii) the Datagram Congestion Control Protocol (DCCP); currently
   under development; see [FHK02]

   (iii) The Stream Control Transmission Protocol (SCTP) under
   development [SCTP]. SCTP is by default reliable, but has the
   capability to operate in unreliable and partially reliable modes
   [PR-SCTP]. See [D03] for description of its potential use in flow

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   (iv) collector-based rate reconfiguration, described below.

   7.7 Collector-based Rate Reconfiguration

   Since collector-based rate reconfiguration is a new proposal, this
   draft will discuss it in some detail.

   The collector can detect congestion loss along the path from the
   exporting device to the collector by observing packet loss,
   manifest as gaps in the sequence numbers, or the absence of packets
   for a period of time. The server can run an appropriate
   congestion-control algorithm to compute a new export rate limit,
   then reconfigure the export process with the new rate.  This is an
   attractive alternative to requiring the export process to receive
   acknowledgment packets.  Implementing the congestion control
   algorithm in the collector has the added advantages of flexibility
   in adapting the sending rate and the ability to incorporate new
   congestion-control algorithms as they become available.

   7.7.1 Changing the Export Rate and Other Rates

   Forcing the export process to discard excess reports is an
   effective control under short term congestion. Alternatively, the
   selection process could be reconfigured to select fewer packets, or
   the reporting process could be reconfigured to send smaller reports
   on each selected packet. This may be a more appropriate reaction to
   long-term congestion. In some cases, a collector may receive
   measurement packets due to more than one export process, and could
   decide to reduce the export or other rates associated with one
   export process rather than another, in order to prioritize the
   measurement data.  This type of flexibility is valuable for network
   operators that collect measurement data from multiple locations to
   drive multiple applications.

   7.7.2 Notions of Fairness

   In some cases, it may be reasonable to allow the collector to have
   flexibility in deciding how aggressively to respond to congestion.
   For example, the exporting entity and the collector may have a very
   small round-trip time relative to other traffic.  Conventional
   TCP-friendly congestion control would allocate a very large share
   of the bandwidth to the PSAMP export traffic.  Instead, the
   collector could apply an algorithm that reacts more aggressively to
   congestion to give a larger share of the bandwidth to other traffic
   (with larger RTTs).

   In other cases, the measurement packets may require a larger share
   of the bandwidth than other flows.  For example, consider a link
   that carries tens of thousands of flows, including some non

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   TCP-friendly DoS attack traffic.  Restricting the PSAMP traffic to
   a fair share allocation may be too restrictive, and might limit the
   collection of the data necessary to diagnose the DoS attack which
   overloads links over which measurement packets are carried. In
   order to maintain report collection during periods of congestion,
   PSAMP report streams may claim more than a fair share of link
   bandwidth, provided the number of report streams in competition
   with fair sharing traffic is limited. The collector could also
   employ policies that allocate bandwidth in certain proportions
   amongst different measurement processes.

   7.7.3 Behavior Under Overload and Failure

   The congestion control algorithm has to be robust to severe
   overload or complete loss of connectivity between the exporting
   entity and the collector, and also to the failure of exporting
   entity or the collector. For example, in a scenario where the
   collector is unable to reconfigure the export rate because of loss
   of reverse (collector to exporting entity) connectivity, it is
   desirable for the exporting entity to reduce the export rate
   autonomously.  Similarly, if no measurement packets reach the
   collector because of loss of forward connectivity, the collector
   should not react to this by increasing the export rate. This
   problem may be solved through periodic heartbeat packets in both
   directions (i.e., measurement packets in the forward direction,
   configuration refresh messages in the reverse direction). This
   allows each side to detect a loss in connectivity or outright
   failure and to react appropriately.

8 Configuration and Management

   A key requirement for PSAMP is the easy reconfiguration of the
   parameters of the measurement process: those for selection, packet
   reports and export. Examples are (i) support of measurement based
   applications that want to drill-down on traffic detail in
   real-time; (ii) collector-based rate reconfiguration.

   To facilitate reconfiguration and retrieval of parameters, they are
   to reside in a Management Information Base (MIB). Mandatory
   configuration, capabilities and monitoring objects will cover all
   minimum required (MUST) PSAMP functionality.

   Secondary objects will cover the recommended PSAMP functionality
   (SHOULD), and MUST be provided only when such functionality is
   offered by an entity. Such PSAMP functionality includes
   configuration of offered selectors, composite selectors, multiple
   measurement processes, and report format including the choice of
   fields to be reported. For further details concerning the PSAMP MIB,
   see [DRC03].

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   PSAMP requires a uniform mechanism with which to access and
   configure the MIB. SNMP access MUST be provided by the entity
   hosting the MIB.

9 Feasibility and Complexity

   In order for PSAMP to be supported across the entire spectrum of
   networking equipment, it must be simple and inexpensive to
   implement.  One can envision easy-to-implement instances of the
   mechanisms described within this draft. Thus, for that subset of
   instances, it should be straightforward for virtually all system
   vendors to include them within their products. Indeed, sampling and
   filtering operations are already realized in available equipment.

   Here we give some specific arguments to demonstrate feasibility and
   comment on the complexity of hardware implementations. We stress
   here that the point of these arguments is not to favor or recommend
   any particular implementation, or to suggest a path for
   standardization, but rather to demonstrate that the set of possible
   implementations is not empty.

   9.1 Feasibility

   9.1.1 Filtering

   Filtering consists of a small number of mask (bit-wise logical),
   comparison and range (greater than) operations.  Implementation of
   at least a small number of such operations is straightforward. For
   example, filters for security access control lists (ACLs) are
   widely implemented. This could be as simple as an exact match on
   certain fields, or involve more complex comparisons and ranges.

   9.1.2 Sampling

   Sampling based on either counters (counter set, decrement, test for
   equal to zero) or range matching on the hash of a packet (greater
   than) is possible given a small number of selectors, although there
   may be some differences in ease of implementation for hardware
   vs. software platforms.

   9.1.3 Hashing

   Hashing functions vary greatly in complexity.  Execution of a small
   number of sufficient simple hash functions is implementable at line
   rate. Concerning the input to the hash function, hop-invariant IP
   header fields (IP address, identification) and TCP/UDP header
   fields (port numbers, TCP sequence number) drawn from the first 40
   bytes of the packet have been found to possess a considerable
   variability; see [DuGr01].

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   9.1.4 Reporting

   The simplest packet report would duplicate the first n bytes of the
   packet. However, such an uncompressed format may tax the bandwidth
   available to the reporting process for high sampling rates;
   reporting selected fields would save on this bandwidth. Thus there
   is a trade-off between simplicity and bandwidth limitations.

   9.1.5  Export

   Ease of exporting measurement packets depends on the system
   architecture. Most systems should be able to support export
   by insertion of measurement packets, even through the software

   9.2 Potential Hardware Complexity

   We now comment on the complexity of possible hardware
   implementations. Achieving low constants for performance while
   minimizing hardware resources is, of course, a challenge,
   especially at very high clock frequencies. Most of these
   operations, however, are very basic and their implementations very
   well understood; in fact, the average ASIC designer simply uses
   canned library instances of these operations rather than design
   them from scratch. In addition, networking equipment generally does
   not need to run at the fastest clock rates, further reducing the
   effort required to get reasonably efficient implementations.

   Simple bit-wise logical operations are easy to implement in
   hardware.  Such operations (NAND/NOR/XNOR/NOT) directly translate
   to four-transistor gates.  Each bit of a multiple-bit logical
   operation is completely independent and thus can be performed in
   parallel incurring no additional performance cost above a single
   bit operation.

   Comparisons (EQ/NEQ) take O(lg(M)) stages of logic, where M is the
   number of bits involved in the comparison.  The lg(M) is required
   to accumulate the result into a single bit.

   Greater than operations, as used to determine whether a hash falls
   in a selection range, are a determination of the most significant
   not-equivalent bit in the two operands.  The operand with that
   most-significant-not-equal bit set to be one is greater than the
   other.  Thus, a greater than operation is also an O(lg(M)) stages
   of logic operation. Optimized implementations of arithmetic
   operations are also O(lg(M)) due to propagation of the carry bit.

   Setting a counter is simply loading a register with a state.  Such
   an operation is simple and fast O(1).  Incrementing or decrementing
   a counter is a read, followed by an arithmetic operation followed
   by a store.  Making the register dual-ported does take additional

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   space, but it is a well-understood technique.  Thus, the
   increment/decrement is also an O(lg(M)) operation.

   Hashing functions come in a variety of forms.  The computation
   involved in a standard Cyclic Redundancy Code (CRC) for example are
   essentially a set of XOR operations, where the intermediate result
   is stored and XORed with the next chunk of data.  There are only
   O(1) operations and no log complexity operations.  Thus, a simple
   hash function, such as CRC or generalizations thereof, can be
   implemented in hardware very efficiently.

   At the other end of the range of complexity, the MD5 function uses
   a large number of bit-wise conditional operations and arithmetic
   operations.  The former are O(1) operations and the latter are
   O(lg(M)). MD5 specifies 256 32b ADD operations per 16B of input
   processed.  Consider processing 10Gb/sec at 100MHz (this processing
   rate appears to be currently available). This requires processing
   12.5B/cycle, and hence at least 200 adders, a sizeable
   number. Because of data dependencies within the MD5 algorithm, the
   adders cannot be simply run in parallel, thus requiring either
   faster clock rates and/or more advanced architectures. Thus
   selection hashing functions as complex as MD5 may be precluded from
   ubiquitous use at full line rate. This motivates exploring the use
   of selection hash functions with complexity somewhere between that
   of MD5 and CRC. However, identification hashing with MD5 on only
   selected packets is feasible at a sufficiently low sampling frequency.

10 Applications

   We first describe several representative operational applications
   that require traffic measurements at various levels of temporal and
   spatial granularity. Some of the goals here appear similar to those
   of IPFIX, at least in the broad classes of applications
   supported. However, there are two major differences:

       - PSAMP aims for ubiquitous deployment of packet measurement,
       including devices that are not expected to support IPFIX. This
       offers broader reach for existing applications.
       - PSAMP can support new applications through the type of packet
       selectors that it supports

   10.1 Baseline Measurement and Drill Down

   Packet sampling is ideally suited to determine the composition of
   the traffic across a network. The approach is to enable measurement
   on a cut-set of the network links such that each packet entering
   the network is seen at least once, for example, on all ingress
   links. Unfiltered sampling with a relatively low frequency
   establishes baseline measurements of the network traffic. Reports
   include packet attributes of common interest: source and
   destination address and port numbers, prefix, protocol number, type

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   of service, etc. Traffic matrices are indicated by reporting source
   and destination AS matrices. Absolute traffic volumes are estimated
   by renormalizing the sampled traffic volumes through division by
   either the target sampling frequency, or the attained sampling
   frequency (as derived by interface packet counters included in the
   report stream)

   Suppose an operator or a measurement based application detects an
   interesting subset of a packet stream, as identified by a
   particular packet attribute. Real-time drill-down to that subset is
   achieved by instantiating a new measurement process on the same
   packet stream from which the subset was reported. The selection
   process of the new measurement process filters according to the
   attribute of interest, and composes with sampling if necessary to
   manage the frequency of packet selection.

   10.2 Passive Performance Measurement

   Hash-based sampling enables the tracking of the performance
   experience by customer traffic, customers identified by a list of
   source or destination prefixes, or by ingress or egress
   interfaces. Operational uses include the verification of Service
   Level Agreements (SLAs), and troubleshooting following a customer

   In this application, Trajectory Sampling is enabled at all network
   ingress and egress interfaces. The label hash is used to match up
   ingress and egress samples. Rates of loss in transit between
   ingress and egress are estimated from the proportion of
   trajectories for which no egress report is received. Note loss of
   customer packets is distinguishable from loss of packet reports
   through use of report sequence numbers. Assuming synchronization of
   clock between different entities, delay of customer traffic across
   the network may also be measured.

   Extending hash-selection to all interfaces in the network would
   enable attribution of poor performance to individual network links.

   10.3 Troubleshooting

   PSAMP can also be used to diagnose problems whose occurrence is
   evident from aggregate statistics, per interface utilization and
   packet loss statistics.  These statistics are typically moving
   averages over relatively long time windows, e.g., 5 minutes, and
   serve as a coarse-grain indication of operational health of the
   network. The most common method of obtaining such measurements are
   through the appropriate SNMP MIBs (MIB-II and vendor-specific

   Suppose an operator detects a link that is persistently overloaded
   and experiences significant packet drop rates. There is a wide

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   range of potential causes: routing parameters (e.g., OSPF link
   weights) that are poorly adapted to the traffic matrix, e.g.,
   because of a shift in that matrix; a denial of service attack or a
   flash crowd; a routing problem (link flapping). In most cases,
   aggregate link statistics are not sufficient to distinguish between
   such causes, and to decide on an appropriate corrective action. For
   example, if routing over two links is unstable, and the links flap
   between being overloaded and inactive, this might be averaged out
   in a 5 minute window, indicating moderate loads on both links.

   Baseline PSAMP measurement the congested link, as described in
   Section 10.1, enables measurements that are fine grained in both
   space and time. The operator has to be able to determine how many
   bytes/packets are generated for each source/destination address,
   port number, and prefix, or other attributes, such as protocol
   number, MPLS forwarding equivalence class (FEC), type of service,
   etc. This allows to pinpoint precisely the nature of the offending
   traffic. For example, in the case of a DDoS attack, the operator
   would see a significant fraction of traffic with an identical
   destination address.

   In certain circumstances, precise information about the spatial
   flow of traffic through the network domain is required to detect
   and diagnose problems and verify correct network behavior. In the
   case of the overloaded link, it would be very helpful to know the
   precise set of paths that packets traversing this link follow. This
   would readily reveal a routing problem such as a loop, or a link
   with a misconfigured weight. More generally, complex diagnosis
   scenarios can benefit from measurement of traffic intensities (and
   other attributes) over a set of paths that is constrained in some
   way. For example, if a multihomed customer complains about
   performance problems on one of the access links from a particular
   source address prefix, the operator should be able to examine in
   detail the traffic from that source prefix which also traverses the
   specified access link towards the customer.

   While it is in principle possible to obtain the spatial flow of
   traffic through auxiliary network state information, e.g., by
   downloading routing and forwarding tables from routers, this
   information is often unreliable, outdated, voluminous, and
   contingent on a network model. For operational purposes, a direct
   observation of traffic flow is more reliable, as it does not depend
   on any such auxiliary information. For example, if there was a bug
   in a router's software, direct observation would allow to diagnose
   the effect of this bug, while an indirect method would not.

11 Security Considerations.

   Security considerations are addressed in:

   - Section 3.1: item Robust Selection

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   - Section 3.3: item Secure Export
   - Section 3.4: item Secure Configuration

12 References

   [B88] R.T. Braden, A pseudo-machine for packet monitoring and
   statistics, in Proc ACM SIGCOMM 1988

   [ClPB93] K.C. Claffy, G.C. Polyzos, H.-W. Braun, Application of
   Sampling Methodologies to Network Traffic Characterization,
   Proceedings of ACM SIGCOMM'93, San Francisco, CA, USA, September
   13-17, 1993

   [DRC03] T. Dietz, D. Romascanu, B. Claise, Definitions of Managed
   Objects for Packet Sampling, Internet Draft,
   draft-ietf-psamp-mib-00.txt, work in progress, June 2003.

   [D03] M. Djernaes, Cisco Systems NetFlow Services Export Version 9
   Transport, Internet Draft,
   draft-djernaes-netflow-9-transport-00.txt, work in progress,
   February 2003

   [DuGr01] N. G. Duffield and M. Grossglauser, Trajectory Sampling for
   Direct Traffic Observation, IEEE/ACM Trans. on Networking, 9(3), .
   280-292, June 2001.

   [FHK02] S. Floyd, M. Handley. E. Kohler, Problem Statement for
   DCCP, Internet Draft draft-ietf-dccp-problem-00.txt, work in
   progress, October 2002.

   [LCTV02] W.S. Lai, B.Christian, R.W. Tibbs, S. Van den Berghe, A
   Framework for Internet Traffic Engineering Measurement, Internet
   Draft draft-ietf-tewg-measure-05.txt, work in progress, February

   [PPM01] P. Phaal, S. Panchen, N. McKee, InMon Corporation's
   sFlow: A Method for Monitoring Traffic in Switched and Routed
   Networks, RFC 3176, September 2001

   [PAMM98] V. Paxson, G. Almes, J. Mahdavi, M. Mathis,  Framework for
   IP Performance Metrics, RFC 2330, May 1998

   [QZCZ03] J. Quittek, T. Zseby, B. Claise, S. Zander, Requirements
   for IP Flow Information Export, Internet Draft
   draft-ietf-ipfix-reqs-10.txt, work in progress, June 2003.

   [SPSJTKS01] A. C. Snoeren, C. Partridge, L. A. Sanchez, C. E. Jones,
   F. Tchakountio, S. T. Kent, W. T. Strayer, Hash-Based IP Traceback,
   Proc. ACM SIGCOMM 2001, San Diego, CA, September 2001.

   [RFC2960] Stewart, R. (ed.) "Stream Control Transmission Protocol",

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   RFC 2960, October 2000

   [PR-SCTP] Stewart, R, "SCTP Partial Reliability Extension",
   Internet Draft, draft-stewart-tsvwg-prsctp-01.txt, work in
   progress, June 2003.

   [ZMRD03] T. Zseby, M. Molina, F. Raspall, N.G. Duffield, Sampling
   and Filtering Techniques for IP Packet Selection, Internet Draft
   draft-ietf-psamp-sample-tech-01.txt, work in progress, March 2003.

13 Authors' Addresses

   Derek Chiou
   Avici Systems
   101 Billerica Ave
   North Billerica, MA 01862
   Phone: +1 978-964-2017
   Email: dchiou@avici.com

   Benoit Claise
   Cisco Systems
   De Kleetlaan 6a b1
   1831 Diegem
   Phone: +32 2 704 5622
   Email: bclaise@cisco.com

   Nick Duffield
   AT&T Labs - Research
   Room B-139
   180 Park Ave
   Florham Park NJ 07932, USA
   Phone: +1 973-360-8726
   Email: duffield@research.att.com

   Albert Greenberg
   AT&T Labs - Research
   Room A-161
   180 Park Ave
   Florham Park NJ 07932, USA
   Phone: +1 973-360-8730
   Email: albert@research.att.com

   Matthias Grossglauser
   School of Computer and Communication Sciences
   1015 Lausanne
   Email: matthias.grossglauser@epfl.ch

   Peram Marimuthu

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   Cisco Systems
   170, W. Tasman Drive
   San Jose, CA 95134
   Phone: (408) 527-6314
   Email: peram@cisco.com

   Jennifer Rexford
   AT&T Labs - Research
   Room A-169
   180 Park Ave
   Florham Park NJ 07932, USA
   Phone: +1 973-360-8728
   Email: jrex@research.att.com

   Ganesh Sadasivan
   Cisco Systems
   170 W. Tasman Drive
   San Jose, CA 95134
   Phone: (408) 527-0251
   Email: gsadasiv@cisco.com

14 Intellectual Property Statement

   AT&T Corporation may own intellectual property applicable to this
   contribution. The IETF has been notified of AT&T's licensing intent
   for the specification contained in this document. See
   http://www.ietf.org/ietf/IPR/ATT-GENERAL.txt for AT&T's IPR

15 Full Copyright Statement

   Copyright (C) The Internet Society (2003).  All Rights Reserved.

   This document and translations of it may be copied and furnished to
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   must be followed, or as required to translate it into languages
   other than English.

   The limited permissions granted above are perpetual and will not be
   revoked by the Internet Society or its successors or assigns.

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