Large-Scale Broadband Measurement Use Cases
draft-ietf-lmap-use-cases-01

INTERNET-DRAFT                                              Marc Linsner
Intended Status: Informational                             Cisco Systems
Expires: June 7, 2014                                     Philip Eardley
                                                        Trevor Burbridge
                                                                      BT
                                                          Frode Sorensen
                                                                     NPT
                                                        December 4, 2013

              Large-Scale Broadband Measurement Use Cases 
                      draft-ietf-lmap-use-cases-01

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
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Copyright and License Notice

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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 Regulators . . . . . . . . . . . . . . . . . . . . . . . . .  4
   3  Details of ISP Use Case . . . . . . . . . . . . . . . . . . . .  5
     3.1 Existing Capabilities and Shortcomings . . . . . . . . . . .  5
     3.2 Understanding the quality experienced by customers . . . . .  6
     3.3 Understanding the impact and operation of new devices and 
         technology . . . . . . . . . . . . . . . . . . . . . . . . .  7
     3.4 Design and planning  . . . . . . . . . . . . . . . . . . . .  8
     3.5 Identifying, isolating and fixing network problems . . . . .  9
     3.6 Conclusions  . . . . . . . . . . . . . . . . . . . . . . . . 11
   4  Details of Regulator Use Case . . . . . . . . . . . . . . . . . 12
     4.1 Promoting competition through transparency . . . . . . . . . 12
     4.2 Promoting broadband deployment . . . . . . . . . . . . . . . 13
     4.3 Monitoring "net neutrality"  . . . . . . . . . . . . . . . . 14
   5  Security Considerations . . . . . . . . . . . . . . . . . . . . 14
   6  IANA Considerations . . . . . . . . . . . . . . . . . . . . . . 15
   Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
   Normative References . . . . . . . . . . . . . . . . . . . . . . . 15
   Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 17

 

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1  Introduction

   Large-scale Measurement of Broadband Performance (LMAP) includes 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

   The LMAP architecture utilizes metrics for instructions on how to
   execute a particular measurement. Although layer 2 specific metrics
   can and will be defined, from the LMAP perspective, there is no
   difference between fixed service and mobile (cellular) service used
   for Internet access.  Hence, like measurements will take place on
   both fixed and mobile networks.  Fixed services, commonly known as
   "Last Mile" include technologies like DSL, Cable, and Carrier
   Ethernet.  Mobile services include all those advertised as 2G, 3G,
   4G, and LTE.  A metric defined to measure over-the-top services will
   execute similarly on all layer 2 technologies. The LMAP architecture
   covers networks utilizing both IPv4 and IPv6.

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.
 

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      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 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 Regulators

   Regulators in jurisdictions around the world are responding to
   consumers' adoption of Internet access services for traditional
   telecommunications and media services by promoting competition among
   providers of electronic communications, to ensure that users derive
   maximum benefit in terms of choice, price, and quality.

   Some jurisdictions have responded to a need for greater information
   about Internet access service 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,
   European Commission's Quality of Broadband Services in the EU reports
   and a growing list of other programs employ a diverse set of
   operational and technical approaches to gathering data 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 Internet access service
   providers, diverse technical solutions, geographic and regional
   distributions, and marketed and provisioned levels and combinations
   of broadband Internet access services. In some jurisdictions, the
   role of measuring is provided by a measurement provider.

   Measurement providers measure network performance from users towards
   multiple content and application providers, included dedicated test
 

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   measurement servers, to show a performance of the actual Internet
   access service provided by different ISPs. Users need to know the
   performance that are achieving from their own ISP. In addition, they
   need to know the performance of other ISPs of same location as
   background information for selecting their ISP. Measurement providers
   will provide measurement results with associated measurement methods
   and measurement metrics.

   From a consumer perspective, the differentiation between fixed and
   mobile (cellular) Internet access services is blurring as the
   applications used are very similar. Hence, regulators are measuring
   both fixed and mobile Internet access services.

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

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

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
 

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   network to confirm the operation of the user Internet access line.
   These tests can be helpful for a user to understand whether their
   Internet access 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", i.e., 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
   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, i.e., 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
 

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   on the customer's ordinary 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
      that represent the QoE

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

3.3 Understanding the impact and operation of new devices and technology

   Another type of measurement is to test new capabilities and services
   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:
 

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      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.

3.4 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. 

   With better information, capacity planning and network design can be
   more effective. Such planning typically uses simulations to emulate
   the measured performance of the current network and understand the
   likely impact of new capacity and potential changes to the topology.
   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'. What-if
   simulations could help quantify the advantage that a new technology
   brings and support the business case for larger roll-out. This
   approach should allow good results with measurements from a limited
   panel of customers.

   Another example is that the operator may want to monitor performance
   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.

 

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   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.

   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

3.5 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
 

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   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. The network management tools may use simulations to
   emulate the network and so help identify a fault and assess possible
   solutions.

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

   The characteristics of large scale measurements emerging from these
   examples:

 

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      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.

      8.  Ideally the measurement functionality should be at every
      customer (not just a subset), in order to allow per-line fault
      diagnosis.

3.6 Conclusions

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

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   contract data is commercial or private information and needs to be
   protected.

4  Details of Regulator Use Case

4.1 Promoting competition through transparency

   Competition plays a vital role in regulation of the electronic
   communications markets. For competition to successfully discipline
   operators' behaviour in the interests of their customers, end users
   must be fully aware of the characteristics of the ISPs' access
   offers. In some jurisdictions regulators mandate transparent
   information made available about service offers.

   End users need effective transparency to be able to make informed
   choices throughout the different stages of their relationship with
   ISPs, when selecting Internet access service offers, and when
   considering switching service offer within an ISP or to an
   alternative ISP. Quality information about service offers could
   include speed, delay, and jitter. Regulators can publish such
   information to facilitate end users' choice of service provider and
   offer. It may also help content, application, service and device
   providers develop their Internet offerings.

   The published information needs to be:

      o  Accurate - the measurement results must be correct and not
      influenced by errors or side effects. The results should be
      reproducible and consistent over time.

      o  Comparable - common metrics should be used across different
      ISPs and service offerings so that measurement results can be
      compared.

      o  Meaningful - the metrics used for measurements need to reflect
      what end users value about their broadband Internet access service

      o  Reliable - the number and distribution of measurement agents,
      and the statistical processing of the raw measurement raw data,
      needs to be appropriate

   A set of measurement parameters and associated measurement methods
   are used over time, e.g. speed, delay, and jitter. Then the
   measurement raw data are collected and go through statistical post-
   processing before the results can be published in an Internet access
   service quality index to facilitate end users' choice of service
   provider and offer.
 

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   A measurement system that monitor Internet access services and
   collect quality information can typically consist of a number of
   measurement probes and one or more test servers located at peering
   points. The system can be operated by a regulator or a measurement
   provider.  Number and distribution of probes follows specific
   requirements depending on the scope and the desired statistical
   reliability of the measurement campaign. 

   Further, the regulator may consider making measurement tools
   available for end users, so that they can monitor the performance of
   their own broadband Internet access service. They might use this
   information to check that the performance meets that specified in
   their contract or to understand whether their current subscription is
   the most appropriate. Such end user scenarios are not the focus of
   the initial LMAP charter, although it is expected that the mechanisms
   developed would be readily applied.

4.2 Promoting broadband deployment

   Governments sometimes set strategic goals for high-speed broadband
   penetration as an important component of the economic, cultural and
   social development of the society. To evaluate the effect of the
   stimulated growth over time, broadband Internet access take-up and
   penetration of high-speed access can be monitored through measurement
   campaigns.

   An example of such an initiative is the "Digital Agenda for Europe"
   which was adopted in 2010, to achieve universal broadband access. The
   goal is to achieve by 2020, access for all Europeans to Internet
   access speeds of 30 Mbps or above, and 50% or more of European
   households subscribing to Internet connections above 100 Mbps.

   To monitor actual broadband Internet access performance in a specific
   country or a region, extensive measurement campaigns are needed. A
   panel can be built based on operators and packages in the market,
   spread over urban, suburban and rural areas. Probes can then be
   distributed to the participants of the campaign.

   Periodic tests running on the probes can for example measure actual
   speed at peak and off-peak hours, but also other detailed quality
   metrics like delay and jitter. Collected data goes afterwards through
   statistical analysis, deriving estimates for the whole population
   which can then be presented and published regularly.

   Using a harmonized or standardised measurement methodology, or even a
   common quality measurement platform, measurement results could also
   be used for benchmarking of providers and/or countries.
 

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4.3 Monitoring "net neutrality"

   Regulatory approaches related to net neutrality and the open Internet
   has been introduced in some jurisdictions. Examples of such are the
   Internet policy as outlined by the FCC Preserving the Open Internet
   Report and Order [FCC R&O] and the Body of European Regulators for
   Electronic Communications Guidelines for quality of service [BEREC
   Guidelines]. The exact definitions and requirements vary from one
   jurisdiction to another; the comments below provide some hints about
   the potential role of measurements.

   Net neutrality regulations do not necessarily require every packet to
   be treated equally. Typically they allow "reasonable" traffic
   management (for example if there is exceptional congestion) and allow
   "specialized services" in parallel to, but separate from, ordinary
   Internet access (for example for facilities-based IPTV). A regulator
   may want to monitor such practices as input to the regulatory
   evaluation. However, these concepts are evolving and differ across
   jurisdictions, so measurement results should be assessed with
   caution.

   A regulator could monitor departures from application agnosticism
   such as blocking or throttling of traffic from specific applications,
   and preferential treatment of specific applications. A measurement
   system could send, or passively monitor, application-specific traffic
   and then measure in detail the transfer of the different packets.
   Whilst it is relatively easy to measure port blocking, it is a
   research topic how to detect other types of differentiated treatment.
    The paper, "Glasnost: Enabling End Users to Detect Traffic
   Differentiation" [M-Labs NSDI 2010] and follow-on tool "Glasnost"
   [Glasnost] are examples of work in this area.

   A regulator could also monitor the performance of the broadband
   service over time, to try and detect if the specialized service is
   provided at the expense of the Internet access service. Comparison
   between ISPs or between different countries may also be relevant for
   this kind of evaluation.

5  Security Considerations

   This informational document provides an overview of the use cases for
   LMAP and so does not, in itself, raise any security issues.

   The framework document [framework] discusses the potential security,
   privacy (data protection) and business sensitivity issues that LMAP
   raises. The main threats are:

 

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      1.  a malicious party that gains control of Measurement Agents to
      launch DoS attacks at a target, or to alter (perhaps subtly)
      Measurement Tasks in order to compromise the end user's privacy,
      the business confidentiality of the network, or the accuracy of
      the measurement system.

      2.  a malicious party that intercepts or corrupts the Measurement
      Results &/or other information about the Subscriber, for similar
      nefarious purposes.

      3.  a malicious party that uses fingerprinting techniques to
      identify individual end users, even from anonymized data

      4.  a measurement system that does not obtain the end user's
      informed consent, or fails to specify a specific purpose in the
      consent, or uses the collected information for secondary uses
      beyond those specified.

      5.  a measurement system that is vague about who is the "data
      controller": the party legally responsible for privacy (data
      protection).

      The [framework] also considers some potential mitigations of these
      issues. They will need to be considered by an LMAP protocol and
      more generally by any measurement system.

6  IANA Considerations

   None

Contributors

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

   James Miller         jamesmilleresquire@gmail.com

   Rachel Huang         rachel.huang@huawei.com

Normative References

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

 

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   [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

   [framework] Eardley, P., Morton, A., Bagnulo, M., Burbridge, T.,
              Aitken, P., Akhter, A.  "A framework for large-scale
              measurement platforms (LMAP)",
              http://datatracker.ietf.org/doc/draft-ietf-lmap-framework/

   [FCC R&O]  United States Federal Communications Commission, 10-201,
              "Preserving the Open Internet, Broadband Industries
              Practices, Report and Order",
              http://hraunfoss.fcc.gov/edocs_public/attachmatch/FCC-10-
              201A1.pdf

   [BEREC Guidelines] Body of European Regulators for Electronic
              Communications, "BEREC Guidelines for quality of service
              in the scope of net neutrality",
              http://berec.europa.eu/eng/document_register/
              subject_matter/berec/download/0/1101-berec-guidelines-for-
              quality-of-service-_0.pdf

   [M-Labs NSDI 2010] M-Lab, "Glasnost: Enabling End Users to Detect
              Traffic Differentiation",
              http://www.measurementlab.net/download/AMIfv945ljiJXzG-
              fgUrZSTu2hs1xRl5Oh-rpGQMWL305BNQh-BSq5oBoYU4a7zqXOvrztpJh
              K9gwk5unOe-fOzj4X-vOQz_HRrnYU-aFd0rv332RDReRfOYkJuagysst
              N3GZ__ lQHTS8_UHJTWkrwyqIUjffVeDxQ/

   [Glosnast] M-Lab tool "Glasnost", http://mlab-live.appspot.com/tools/
              glasnost

 

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Authors' Addresses

              Marc Linsner
              Cisco Systems, Inc.
              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

              Frode Sorensen
              Norwegian Post and Telecommunications Authority (NPT)
              Lillesand
              Norway

              Email: frode.sorensen@npt.no

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