INTERNET-DRAFT                                              Marc Linsner
Intended Status: Informational                             Cisco Systems
Expires: August 29, 2013                                  Philip Eardley
                                                        Trevor Burbridge
                                                                      BT
                                                       February 25, 2013


              Large-Scale Broadband Measurement Use Cases
                    draft-linsner-lmap-use-cases-02


Abstract

   Measuring broadband performance on a large scale is important for
   network diagnostics by providers and users, as well for as public
   policy.  To conduct such measurements, user networks gather data,
   either on their own initiative or instructed by a measurement
   controller, and then upload the measurement results to a designated
   measurement server.  Understanding the various scenarios and users of
   measuring broadband performance is essential to development of the
   system requirements.  The details of the measurement metrics
   themselves are beyond the scope of this document.


Status of this Memo

   This Internet-Draft is submitted to IETF in full conformance with the
   provisions of BCP 78 and BCP 79.

   Internet-Drafts are working documents of the Internet Engineering
   Task Force (IETF), its areas, and its working groups.  Note that
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   Internet-Drafts.

   Internet-Drafts are draft documents valid for a maximum of six months
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   time.  It is inappropriate to use Internet-Drafts as reference
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   http://www.ietf.org/1id-abstracts.html

   The list of Internet-Draft Shadow Directories can be accessed at
   http://www.ietf.org/shadow.html






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Copyright and License Notice

   Copyright (c) 2013 IETF Trust and the persons identified as the
   document authors. All rights reserved.

   This document is subject to BCP 78 and the IETF Trust's Legal
   Provisions Relating to IETF Documents
   (http://trustee.ietf.org/license-info) in effect on the date of
   publication of this document. Please review these documents
   carefully, as they describe your rights and restrictions with respect
   to this document. Code Components extracted from this document must
   include Simplified BSD License text as described in Section 4.e of
   the Trust Legal Provisions and are provided without warranty as
   described in the Simplified BSD License.



Table of Contents

   1  Introduction  . . . . . . . . . . . . . . . . . . . . . . . . .  3
     1.1  Terminology . . . . . . . . . . . . . . . . . . . . . . . .  3
   2  Use Cases . . . . . . . . . . . . . . . . . . . . . . . . . . .  3
     2.1 Internet Service Provider (ISP) Use Case . . . . . . . . . .  3
     2.2 End User Network Diagnostics . . . . . . . . . . . . . . . .  4
     2.3 Multi-provider Network Measurements  . . . . . . . . . . . .  4
     2.4 Over the Top Providers . . . . . . . . . . . . . . . . . . .  4
     2.5 Regulators . . . . . . . . . . . . . . . . . . . . . . . . .  5
   3  Details of ISP Use Case . . . . . . . . . . . . . . . . . . . .  6
     3.1 Existing Capabilities and Shortcomings . . . . . . . . . . .  6
     3.2 Understanding the quality experienced by customers . . . . .  6
     3.3 Benchmarking and competitor insight  . . . . . . . . . . . .  8
     3.4 Understanding the impact and operation of new devices and
         technology . . . . . . . . . . . . . . . . . . . . . . . . .  8
     3.5 Design and planning  . . . . . . . . . . . . . . . . . . . .  9
     3.6 Identifying, isolating and fixing network problems . . . . . 11
     3.7 Comparison with the regulator use case . . . . . . . . . . . 12
     3.8 Conclusions  . . . . . . . . . . . . . . . . . . . . . . . . 13
   4  Security Considerations . . . . . . . . . . . . . . . . . . . . 14
   5  IANA Considerations . . . . . . . . . . . . . . . . . . . . . . 14
   6  Contributors  . . . . . . . . . . . . . . . . . . . . . . . . . 14
   7  References  . . . . . . . . . . . . . . . . . . . . . . . . . . 14
     7.1  Normative References  . . . . . . . . . . . . . . . . . . . 14
   Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 15








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1  Introduction

   Large-scale measurement efforts in [LMAP-REQ] describe three use
   cases to be considered in deriving the requirements to be used in
   developing the solution.  This documents attempts to describe those
   use cases in further detail and include additional use cases.

1.1  Terminology

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
   document are to be interpreted as described in RFC 2119 [RFC2119].


2  Use Cases


2.1 Internet Service Provider (ISP) Use Case

   An ISP, or indeed another network operator, needs to understand the
   performance of their networks, the performance of the suppliers
   (downstream and upstream networks), the performance of services, and
   the impact that such performance has on the experience of their
   customers. In addition they may also desire visibility of their
   competitor's networks and services in order to be able to benchmark
   and improve their own offerings. Largely the processes that ISPs
   operate (which are based on network measurement) include:

      o Identifying, isolating and fixing problems in the network,
      services or with CPE and end user equipment. Such problems may be
      common to a point in the network topology (e.g. a single
      exchange), common to a vendor or equipment type (e.g. line card or
      home gateway) or unique to a single user line (e.g. copper
      access). Part of this process may also be helping users understand
      whether the problem exists in their home network or with an over-
      the-top service instead of with their BB product.

      o Design and planning. Through identifying the end user experience
      the ISP can design and plan their network to ensure specified
      levels of user experience. Services may be moved closer to end
      users, services upgraded, the impact of QoS assessed or more
      capacity deployed at certain locations. SLAs may be defined at
      network or product boundaries.

      o Benchmarking and competitor insight. The operation of sample
      panels across competitor products can enable and ISP to assess
      where they play in the market, identify opportunities where other
      products operate different technology, and assess the performance



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      of network suppliers that are common to both operators.

      o Understanding the quality experienced by customers. Alongside
      benchmarking competitors, gaining better insight into the user's
      service through a sample panel of the operator's own customers.
      The end-to-end perspective matters, across home /enterprise
      networks, peering points, CDNs etc.

      o Understanding the impact and operation of new devices and
      technology. As a new product is deployed, or a new technology
      introduced into the network, it is essential that its operation
      and impact on other services is measured. This also helps to
      quantify the advantage that the new technology is bringing and
      support the business case for larger roll-out.

2.2 End User Network Diagnostics

   End users may want to determine whether their network is performing
   according to the specifications (e.g., service level agreements)
   offered by their Internet service provider, or they may want to
   diagnose whether components of their network path are impaired.  End
   users may perform measurements on their own, using the measurement
   infrastructure they provide or infrastructure offered by a third
   party, or they may work directly with their network or application
   provider to diagnose a specific performance problem.  Depending on
   the circumstances, measurements may occur at specific pre-defined
   intervals, or may be triggered manually.  A system administrator may
   perform such measurements on behalf of the user.

2.3 Multi-provider Network Measurements

   As an extension of the first use case, multiple network providers and
   third parties, such as a regulatory body, may collaborate to gather
   network performance data on a one-time or recurring basis, using a
   subset of customers of the service providers.  The form of
   collaboration is beyond the scope of this paper, however it should be
   understood that a data collection platform must serve multiple
   stakeholder interests.

   The main consumer of this use case is someone other than the 'last
   mile' provider.

2.4 Over the Top Providers

   Possibly an extension to the Multi-Provider use case, OTT providers
   have an interest to ensure Quality of Experience (QOE) associated
   with content consumption.  The uniqueness to this use case compared
   to those mentioned above is the feature that the measurement client



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   will run on software based apps and embedded apps such as those found
   in set-top boxes or disc players.  It is assumed that measurement
   tests run by OTT providers would only include the metrics associated
   with layer 3 and up.

   The main consumer of this use case are content providers.

2.5 Regulators

   Regulators in jurisdictions around the world are responding to
   consumers' adoption of broadband technology solution for traditional
   telecommunications and media services by reviewing the historical
   approaches to regulating these industries and services and in some
   cases modifying existing approaches or developing new solutions.

   Some jurisdictions have responded to a perceived need for greater
   information about broadband performance in the development of
   regulatory policies and approaches for broadband technologies by
   developing large-scale measurement programs. Programs such as the
   U.S. Federal Communications Commission's Measuring Broadband America,
   U.K. Ofcom's UK Broadband Speeds reports and a growing list of other
   programs employ a diverse set of operational and technical approaches
   to gathering data in scientifically and statistical robust ways to
   perform analysis and reporting on diverse aspects of broadband
   performance.

   While each jurisdiction responds to distinct consumer, industry, and
   regulatory concerns, much commonality exists in the need to produce
   datasets that are able to compare multiple broadband providers,
   diverse technical solutions, geographic and regional distributions,
   and marketed and provisioned levels and combinations of broadband
   services.

   Regulators role in the development and enforcement of broadband
   policies also require that the measurement approaches meet a high
   level of verifiability, accuracy and fairness to support valid and
   meaningful comparisons of broadband performance

   LMAP standards could answer regulators shared needs by providing
   scalable, cost-effective, scientifically robust solutions to the
   measurement and collection of broadband performance information.

   The main consumer of this use case are regulators








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3  Details of ISP Use Case


3.1 Existing Capabilities and Shortcomings

   In order to get reliable benchmarks some ISPs use vendor provided
   hardware measurement platforms that connect directly to the home
   gateway. These devices typically perform a continuous test schedule,
   allowing the operation of the network to be continually assessed
   throughout the day. Careful design ensures that they do not
   detrimentally impact the home user experience or corrupt the test
   results by testing when the user is also using the Broadband line.
   While the test capabilities of such probes are good, they are simply
   too expensive to deploy on mass scale to enable detailed
   understanding of network performance (e.g. to the granularity of a
   single backhaul or single user line). In addition there is no easy
   way to operate similar tests on other devices (eg set top box) or to
   manage application level tests (such as IPTV) using the same control
   and reporting framework.

   ISPs also use speed and other diagnostic tests from user owned
   devices (such as PCs, tablets or smartphones). These often use
   browser related technology to conduct tests to servers in the ISP
   network to confirm the operation of the user BB access line. These
   tests can be helpful for a user to understand whether their BB line
   has a problem, and for dialogue with a helpdesk. However they are not
   able to perform continuous testing and the uncontrolled device and
   home network means that results are not comparable. Producing
   statistics across such tests is very dangerous as the population is
   self-selecting (e.g. those who think they have a problem).

   Faced with a gap in current vendor offerings some ISPs have taken the
   approach of placing proprietary test capabilities on their home
   gateway and other consumer device offerings (such as Set Top Boxes).
   This also means that different device platforms may have different
   and largely incomparable tests, developed by different company sub-
   divisions managed by different systems.

3.2 Understanding the quality experienced by customers

   Operators want to understand the quality of experience (QoE) of their
   broadband customers. The understanding can be gained through a
   "panel", ie a measurement probe is deployed to a few 100 or 1000 of
   its customers. The panel needs to be a representative sample for each
   of the operator's technologies (FTTP, FTTC, ADSL...) and broadband
   options (80Mb/s, 20Mb/s, basic...), ~100 probes for each. The
   operator would like the end-to-end view of the service, rather than
   (say) just the access portion. So as well as simple network



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   statistics like speed and loss rates they want to understand what the
   service feels like to the customer. This involves relating the pure
   network parameters to something like a 'mean opinion score' which
   will be service dependent (for instance web browsing QoE is largely
   determined by latency above a few Mb/s).

   An operator will also want compound metrics such as "reliability",
   which might involve packet loss, DNS failures, re-training of the
   line, video streaming under-runs etc.

   The operator really wants to understand the end-to-end service
   experience. However, the home network (Ethernet, wifi, powerline) is
   highly variable and outside its control. To date, operators (and
   regulators) have instead measured performance from the home gateway.
   However, mobile operators clearly must include the wireless link in
   the measurement.

   Active measurements are the most obvious approach, ie special
   measurement traffic is sent by - and to - the probe. In order not to
   degrade the service of the customer, the measurement data should only
   be sent when the user is silent, and it shouldn't reduce the
   customer's data allowance. The other approach is passive measurements
   on the customer's real traffic; the advantage is that it measures
   what the customer actually does, but it creates extra variability
   (different traffic mixes give different results) and especially it
   raises privacy concerns.

   From an operator's viewpoint, understanding customers better enables
   it to offer better services. Also, simple metrics can be more easily
   understood by senior managers who make investment decisions and by
   sales and marketing.

   The characteristics of large scale measurements that emerge from
   these examples:

      1.  Averaged data (over say 1 month) is generally ok

      2.  A panel (subset) of only a few customers is OK

      3.  Both active and passive measurements are possible, though the
      former seems easier

      4.  Regularly scheduled tests are fine (providing active tests
      back off if the customer is using the line). Scheduling can be
      done some time ahead ('starting tomorrow, run the following test
      every day').

      5.  The operator needs to devise metrics and compound measures



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      that represent the QoE

      6.  End-to-end service matters, and not (just) the access link
      performance

3.3 Benchmarking and competitor insight

   An operator may want to check that the results reported by the
   regulator match its own belief about how its network is performing.
   There is quite a lot of variation in underlying line performance for
   customers on (say) a nominal 20Mb/s service, so it is possible for
   two panels of ~100 probes to produce different results.

   An operator may also want more detailed understanding of its
   competitors, beyond that reported by the regulator - probably by
   getting a third party to establish a panel of probes in its rival
   ISPs. Measurements could, for example, help an operator: target its
   marketing by showing that it's 'best for video streaming' but 'worst
   for web browsing'; gain detailed insight into the strengths and
   weaknesses of different access technologies (DSL vs cable vs
   wireless); understand market segments that it currently doesn't
   serve; and so on.

   The characteristics of large scale measurements that emerge from
   these examples are very similar to the sub use case above:

      1.  Averaged data (over say 1 month) is generally ok

      2.  A panel (subset) of only a few customers is OK

      3.  Both active and passive measurements are possible, though the
      former seems easier

      4.  Regularly scheduled tests are fine (providing active tests
      back off if the customer is using the line). Scheduling can be
      done some time ahead ('starting tomorrow, run the following test
      every day').

      5.  The performance metrics are whatever the operator wants to
      benchmark. As well as QoE measures, it may want to measure some
      network-specific parameters.

      6.  As well as the performance of the access link, the performance
      of different network segments, including end-to-end.

3.4 Understanding the impact and operation of new devices and technology

   Another type of measurement is to test new capabilities and services



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   before they are rolled out. For example, the operator may want to:
   check whether a customer can be upgraded to a new broadband option;
   understand the impact of IPv6 before it makes it available to its
   customers (will v6 packets get through, what will the latency be to
   major websites, what transition mechanisms will be most is
   appropriate?); check whether a new capability can be signaled using
   TCP options (how often it will be blocked by a middlebox? - along the
   lines of some existing experiments) [Extend TCP]; investigate a
   quality of service mechanism (eg checking whether Diffserv markings
   are respected on some path); and so on.

   The characteristics of large scale measurements that emerge from
   these examples are:

      1.  New tests need to be devised that test a prospective
      capability.

      2.  Most of the tests are probably simply: "send one packet and
      record what happens", so an occasional one-off test is sufficient.

      3.  A panel (subset) of only a few customers is probably OK, to
      gain an understanding of the impact of a new technology, but it
      may be necessary to check an individual line where the roll-out is
      per customer.

      4.  An active measurement is needed.

3.5 Design and planning

   Operators can use large scale measurements to help with their network
   planning - proactive activities to improve the network.

   For example, by probing from several different vantage points the
   operator can see that a particular group of customers has performance
   below that expected during peak hours, which should help capacity
   planning. Naturally operators already have tools to help this - a
   network element reports its individual utilisation (and perhaps other
   parameters). However, making measurements across a path rather than
   at a point may make it easier to understand the network. There may
   also be parameters like bufferbloat that aren't currently reported by
   equipment and/or that are intrinsically path metrics.

   It may also be possible to run stress tests for risk analysis, for
   example 'if whizzy new application (or device) becomes popular, which
   parts of my network would struggle, what would be the impact on other
   services and how many customers would be affected'.

   Another example is that the operator may want to monitor performance



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   where there is a service level agreement. This could be with its own
   customers, especially enterprises may have an SLA. The operator can
   proactively spot when the service is degrading near to the SLA limit,
   and get information that will enable more informed conversations with
   the customer at contract renewal.

   An operator may also want to monitor the performance of its
   suppliers, to check whether they meet their SLA or to compare two
   suppliers if it is dual-sourcing. This could include its transit
   operator, CDNs, peering, video source, local network provider (for a
   global operator in countries where it doesn't have its own network),
   even the whole network for a virtual operator.

   Through a better understanding of its own network and its suppliers,
   the operator should be able to focus investment more effectively - in
   the right place at the right time with the right technology. What-if
   tests could help quantify the advantage that a new technology brings
   and support the business case for larger roll-out.

   The characteristics of large scale measurements emerging from these
   examples:

      1.  A key challenge is how to integrate results from measurements
      into existing network planning and management tools

      2.  New tests may need to be devised for the what-if and risk
      analysis scenarios.

      3.  Capacity constraints first reveal themselves during atypical
      events (early warning). So averaging of measurements should be
      over a much shorter time than the sub use case discussed above.

      4.  A panel (subset) of only a few customers is OK for most of the
      examples, but it should probably be larger than the QoE use case
      #1 and the operator may also want to regularly change who is in
      the subset, in order to sample the revealing outliers.

      5.  Measurements over a segment of the network ("end-to-middle")
      are needed, in order to refine understanding, as well as end-to-
      end measurements.

      6.  The primary interest is in measuring specific network
      performance parameters rather than QoE.

      7.  Regularly scheduled tests are fine

      8.  Active measurements are needed; passive ones probably aren't




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3.6 Identifying, isolating and fixing network problems

   Operators can use large scale measurements to help identify a fault
   more rapidly and decide how to solve it.

   Operators already have Test and Diagnostic tools, where a network
   element reports some problem or failure to a management system.
   However, many issues are not caused by a point failure but something
   wider and so will trigger too many alarms, whilst other issues will
   cause degradation rather than failure and so not trigger any alarm.
   Large scale measurements can help provide a more nuanced view that
   helps network management to identify and fix problems more rapidly
   and accurately.

   One example was described in [IETF85-Plenary]. The operator was
   running a measurement panel for reasons discussed in sub use case #1.
   It was noticed that the performance of some lines had unexpectedly
   degraded. This led to a detailed (off-line) investigation which
   discovered that a particular home gateway upgrade had caused a
   (mistaken!) drop in line rate.

   Another example is that occasionally some internal network management
   event (like re-routing) can be customer-affecting (of course this is
   unusual). This affects a whole group of customers, for instance those
   on the same DSLAM. Understanding this will help an operator fix the
   fault more rapidly and/or allow the affected customers to be informed
   what's happening and/or request them to re-set their home hub
   (required to cure some conditions). More accurate information enables
   the operator to reassure customers and take more rapid and effective
   action to cure the problem.

   There may also be problems unique to a single user line (e.g. copper
   access) that need to be identified.

   Often customers experience poor broadband due to problems in the home
   network - the ISP's network is fine. For example they may have moved
   too far away from their wireless access point. Perhaps 80% of
   customer calls about fixed BB problems are due to in-home wireless
   issues. These issues are expensive and frustrating for an operator,
   as they are extremely hard to diagnose and solve. The operator would
   like to narrow down whether the problem is in the home (with the home
   network or edge device or home gateway), in the operator's network,
   or with an over-the-top service. The operator would like two
   capabilities. Firstly, self-help tools that customers use to improve
   their own service or understand its performance better, for example
   to re-position their devices for better wifi coverage. Secondly, on-
   demand tests that can the operator can run instantly - so the call
   centre person answering the phone (or e-chat) could trigger a test



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   and get the result whilst the customer is still on-line session.

   The characteristics of large scale measurements emerging from these
   examples:

      1.  A key challenge is how to integrate results from measurements
      into the operator's existing Test and Diagnostics system.

      2.  Results from the tests shouldn't be averaged

      3.  Tests are generally run on an ad hoc basis, ie specific
      requests for immediate action

      4.  "End-to-middle" measurements, ie across a specific network
      segment, are very relevant

      5.  The primary interest is in measuring specific network
      performance parameters and not QoE

      6.  New tests are needed for example to check the home network (ie
      the connection from the home hub to the set top boxes or to a
      tablets on wifi)

      7.  Active measurements are critical. Passive ones may be useful
      to help understand exactly what the customer is experiencing.

3.7 Comparison with the regulator use case

   Today an increasing number of regulators measure the performance of
   broadband operators. Typically they deploy a few 1000 probes, each of
   which is connected directly to the broadband customer's home gateway
   and periodically measures the performance of that line. The regulator
   ensures they have a set of probes that covers the different ISPs and
   their different technology types and contract speeds, so that they
   can publish statistically-reasonable average performances.
   Publicising the results stimulates competition and so pressurises
   ISPs to improve broadband service.

   The operator use case has similarities but several significant
   differences from the regulator one:

      o  Performance metrics: A regulator and operator are generally
      interested in the same performance metrics. Both would like
      standardised metrics, though this is more important for
      regulators.

      o  Sampling: The regulator wants an average across a
      representative sample of broadband customers (per operator, per



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      type of BB contract). The operator also wants to measure
      individual lines with a problem.

      o  Timeliness: The regulator wants to know the (averaged)
      performance last quarter (say). For fault identification and
      fixing, the operator would like to know the performance at this
      moment and also to instruct a test to be run at this moment (so
      the requirement is on both the testing and reporting). Also, when
      testing the impact of new devices and technology, the operator is
      gaining insight about future performance.

      o  Scheduling: The regulator wants to run scheduled tests
      ('measure download rate every hour'). The operator also wants to
      run one-off tests; perhaps also the result of one test would
      trigger the operator to run a specific follow-up test.

      o  Pre-processing: A regulator would like standard ways of
      processing the collected data, to remove outlier measurements and
      aggregate results, because this can significantly affect the final
      "averaged" result. Pre-processing is not important for an
      operator.

      o  Historic data: The regulator wants to track how the (averaged)
      performance of each operator changes on (say) a quarterly basis.
      The operator would like detailed, recent historic data (eg a
      customer with an intermittent fault over the last week).

      o  Scope: To date, regulators have measured the performance of
      access lines. An operator also wants to understand the performance
      of the home (or enterprise) network and of the end-to-end service,
      ie including backbone, core, peering and transit, CDNs and
      application /content servers.

      o  Control of testing and reporting: The operator wants detailed
      control. The regulator contracts out the measurement caboodle and
      'control' will be via negotiation with its contractor.

      o  Politics: A regulator has to take account of government targets
      (eg UK government: "Our ambition (by 2015) is to provide superfast
      broadband (24Mbps) to at least 90 per cent of premises in the UK
      and to provide universal access to standard broadband with a speed
      of at least 2Mbps.") This may affect the metrics the regulator
      wants to measure and certainly affects how they interpret results.
      The operator is more focused on winning market share.

3.8 Conclusions

   There is a clear need from an ISP point of view to deploy a single



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   coherent measurement capability across a wide number of heterogeneous
   devices both in their own networks and in the home environment. These
   tests need to be able to operate from a wide number of locations to a
   set of interoperable test points in their own network as well as
   spanning supplier and competitor networks.

   Regardless of the tests being operated, there needs to be a way to
   demand or schedule the tests and critically ensure that such tests do
   not affect each other; are not affected by user traffic (unless
   desired) and do not affect the user experience. In addition there
   needs to be a common way to collect and understand the results of
   such tests across different devices to enable correlation and
   comparison between any network or service parameters.

   Since network and service performance needs to be understood and
   analysed in the presence of topology, line, product or contract
   information it is critical that the test points are accurately
   defined and authenticated.

   Finally the test data, along with any associated network, product or
   contract data is commercial or private information and needs to be
   protected.

4  Security Considerations

   TBD


5  IANA Considerations

   TBD

6  Contributors

   The information in this document is partially derived from text
   written by the following contributors:

   James Miller         jamesmilleresquire@gmail.com


7  References

7.1  Normative References

   [RFC2119]  Bradner, S., "Key words for use in RFCs to Indicate
              Requirement Levels", BCP 14, RFC 2119, March 1997.

   [LMAP-REQ] Schulzrinne, H., "Large-Scale Measurement of Broadband



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INTERNET DRAFT               LMAP Use Cases             February 8, 2013


              Performance:  Use Cases, Architecture and Protocol
              Requirements", draft-schulzrinne-lmap-requirements,
              September, 2012

   [IETF85 Plenary] Crawford, S., "Large-Scale Active Measurement of
              Broadband Networks",
              http://www.ietf.org/proceedings/85/slides/slides-85-iesg-
              opsandtech-7.pdf 'example' from slide 18

   [Extend TCP] Michio Honda, Yoshifumi Nishida, Costin Raiciu, Adam
              Greenhalgh, Mark Handley and Hideyuki Tokuda. "Is it Still
              Possible to Extend TCP?" Proc. ACM Internet Measurement
              Conference (IMC), November 2011, Berlin, Germany.
              http://www.ietf.org/proceedings/82/slides/IRTF-1.pdf




Authors' Addresses


              Marc Linsner
              Marco Island, FL
              USA

              EMail: mlinsner@cisco.com

              Philip Eardley
              BT
              B54 Room 77, Adastral Park, Martlesham
              Ipswich, IP5 3RE
              UK

              Email: philip.eardley@bt.com

              Trevor Burbridge
              BT
              B54 Room 77, Adastral Park, Martlesham
              Ipswich, IP5 3RE
              UK

              Email: trevor.burbridge@bt.com









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