SIMPLE                                                        M. Thomson
Internet-Draft                                                    Andrew
Intended status: Informational                          October 23, 2008
Expires: April 26, 2009


Requirements for the Support of Continuously Varying Values in Presence
             draft-thomson-simple-cont-presence-val-req-00

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Abstract

   The attributes of continuous-valued data are examined in respect to
   presence systems.  The limitations of the existing presence system
   with respect to continuous-valued data is examined.  Requirements are
   formulated that would enable the use of the presence system for this
   data, with an emphasis on providing the watcher with a means of
   control over the measurement process.


Table of Contents

   1.  Introduction . . . . . . . . . . . . . . . . . . . . . . . . .  3
     1.1.  Conventions used in this document  . . . . . . . . . . . .  4
   2.  Continous-Valued Data and Measurement  . . . . . . . . . . . .  5
   3.  Logical Model: Presence Sources  . . . . . . . . . . . . . . .  7
   4.  Problem Statement  . . . . . . . . . . . . . . . . . . . . . .  9
     4.1.  Unguided Measurement . . . . . . . . . . . . . . . . . . .  9
     4.2.  Presence Filters . . . . . . . . . . . . . . . . . . . . .  9
     4.3.  Quality  . . . . . . . . . . . . . . . . . . . . . . . . . 10
     4.4.  Watcher Feedback . . . . . . . . . . . . . . . . . . . . . 11
     4.5.  Active and Passive Sources . . . . . . . . . . . . . . . . 12
     4.6.  Triggering Measurement . . . . . . . . . . . . . . . . . . 12
       4.6.1.  Immediate Triggering of Measurement  . . . . . . . . . 13
       4.6.2.  Periodic Triggering of Measurement . . . . . . . . . . 13
       4.6.3.  Value-based Triggering of Measurement  . . . . . . . . 14
   5.  Requirements . . . . . . . . . . . . . . . . . . . . . . . . . 15
     5.1.  Quality Requirements . . . . . . . . . . . . . . . . . . . 15
     5.2.  Immediate Triggering Requirements  . . . . . . . . . . . . 15
     5.3.  Periodic Triggering Requirements . . . . . . . . . . . . . 16
     5.4.  Value-Seeking Requirements . . . . . . . . . . . . . . . . 17
     5.5.  Timeliness Requirements  . . . . . . . . . . . . . . . . . 17
   6.  Security Considerations  . . . . . . . . . . . . . . . . . . . 19
   7.  Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . 20
   8.  References . . . . . . . . . . . . . . . . . . . . . . . . . . 21
     8.1.  Normative References . . . . . . . . . . . . . . . . . . . 21
     8.2.  Informative References . . . . . . . . . . . . . . . . . . 21
   Appendix A.  Presence Agent and Source Interactions  . . . . . . . 23
   Author's Address . . . . . . . . . . . . . . . . . . . . . . . . . 24
   Intellectual Property and Copyright Statements . . . . . . . . . . 25











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1.  Introduction

   The provision of continuously varying parameters using presence
   requires specific support by the presence infrastructure [RFC2778].
   Existing methods assume that perfect information is always available
   to the Presence Agent (PA).  These methods rely on filtering, which
   limit the data provided to a watcher, but do not provide the watcher
   any control over the quality of the actual data.  The current
   presence system is ill-equipped to handle imperfect data.

   Perfect information is available with no delay; perfect information
   is absolutely accurate.  The absence of perfectly accurate
   information, can be inversely characterized as the existence of
   uncertainty.  The measurement of any physical property is subject to
   some degree of uncertainty.  The impact of this depends on the
   purpose that the information is intended for.  If a low standard of
   quality is demanded of the data, the existence of uncertainty might
   be ignored without negative consequences.  However, in some cases
   uncertainty can be significant to the intended use of the
   information.

   Timely availability of information also affects the service provided
   by the PA.  For a continuously varying value, the amount of time
   required to acquire a value increases as the required accuracy
   increases.  The relationship between time and accuracy is likely to
   be non-linear; gains in accuracy follow the law of diminishing
   returns.  Futhermore, as an actual value changes over time, the value
   provided to a watcher could be invalidated by the time the watcher
   receives the information.

   Dealing with imperfect information using presence requires additional
   protocol support.  To properly support continuous-valued data the
   presence system needs to provide a way for a watcher to indicate
   their preferences for data quality and timeliness.  This document
   outlines requirements for presence that enable the use of
   continuously varying parameters.

   Location information is used throughout this document as an exemplary
   example of a continuous-valued datum.  The requirements in this
   document are intended to provide a basis for the definition of
   presence features that support location while giving due
   consideration to support of other continuous variables.

      This document specifies requirements that might already be covered
      by existing publications.  However, to ensure the integrity of the
      overall concept, those requirements are retained.





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1.1.  Conventions used in this document

   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 [RFC2119].

      Paragraphs that are indented like this one contain motivation,
      examples, speculation and other such non-normative gibberish.











































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2.  Continous-Valued Data and Measurement

   Continuous-valued data are defined by this document as having a
   continuous value space.  Therefore, the set of possible values for
   any Continuous-valued datum is infinite.  In contrast, many existing
   presence elements are discrete-valued.  Discrete-valued elements have
   a limited number of possible values.  Continuous-valued data is most
   regularly numerical, or is composed of numerical data.

   Physical properties are a prime example of the use of continuous-
   valued data.  Any value expressed in the SI units (metres, kilograms,
   seconds, ampere, kelvin, mole or candela) and units derived from
   these are within the scope of the general remit of this document.

   Note:  For those with an interest in physics, this document does not
      concern itself with quantum effects.  At the point that presence
      concerns itself with quantum physics, this document is most likely
      long redundant.

   Examples of continuous-valued presence elements could include
   descriptions of the physical characteristics of a presentity or its
   immediate environment.  This could include position in space; weather
   related values such as ambient temperature and wind speed; light or
   noise intensity; remaining battery life of a device; weight and size.
   In contrast, the many elements defined in RFC 4480 [RFC4480] are all
   discrete-valued.

   The act of determining a continuous value is an act of measurement.
   The value that is represented in a presence document is the product
   of a measurement process.  All measurement processes are subject to
   measurement uncertainty, a well-documented phenomenom [ISO.GUM].

   This document applies to the inclusion of continuous-valued data in
   presence, with any of the following constraints:

   1.  The process of measurement has non-zero--or at least non-
       negligible--cost.  Cost can be defined in any number of ways, but
       could include time, processing resources, network utilisation,
       labour or financial.

   2.  The measurement process has limited accuracy, resulting in
       uncertainty that is--or could be--significant.

   Cost and accuracy are somewhat related.  In general, improvements in
   one result in degradation of the other.  For continuous-valued
   information that is not subject to these constraints, some
   requirements from this document could still apply.




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   From the above constraints, one aim of any system that handles such
   continuous-valued data is to minimise both cost and uncertainty using
   different trade-offs.  A common factor amoungst systems that handle
   continuous-valued data is the desire to be able to ignore the effects
   of these constraints.  Where ignorance is not viable, systems exhibit
   a range of traits: iterative measurement collection, caching of
   results, fuzzy logic, maximum likelihood estimation and other forms
   of statistical analysis.

   A significant example of a continuously varying parameter is the
   position of an entity in space, or its location.  Location
   information as an element of presence was established in [RFC4079]
   and a format specified in [RFC4119].  Uncertainty in location
   information, described in more detail in
   [I-D.thomson-geopriv-uncertainty], is a product of the method of
   location generation used and can vary greatly; likewise, the amount
   of time required to ascertain location within specific quality
   constraints is highly variable.

































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3.  Logical Model: Presence Sources

   The entity that measures continuous-valued data--and the process of
   measurement--are crucial in determining the resulting information.
   RFC 3856 [RFC3856] notes that presence data can be sourced by a
   variety of means, but does not attach any significance to the source
   of presence data.  This document adopts a model that distinguishes
   between the PA and the presence source.

      +----------+             +----------+              +---------+
      | Presence |_____________| Presence |______________| Watcher |
      |  Source  |  (Various)  |  Agent   |  (Presence)  |         |
      +----------+             +----------+              +---------+

                          Figure 1: Logical Model

   Specifics of the interaction between presence source and PA are out
   of scope for this document.  There might be formalised protocols, or
   the PA might use unspecified or informal methods to acquire data.
   Formalised exchanges include SIP PUBLISH [RFC3903]; informal
   interactions include those that are briefly described in Section 7 of
   [RFC3856].

   For location information, the GEOPRIV architecture [RFC3693] [[Ed:
   maybe [I-D.barnes-geopriv-lo-sec] instead of or as well as]] defines
   the Location Generator.  The Location Generator is the presence
   source of this model; the entity that generates, or measures, the
   continuous value.  In the GEOPRIV architecture the Location Server is
   the analogue of the PA and the Location Recipient corresponds to the
   Watcher.  Other forms of continuous-valued data might have similarly
   formal architectures and nomenclature.

   In an end-to-end system, the model is potentially iterative.  An
   entity that acts as a presence source to a PA could equally acquire
   its information from a separate source; from a different perspective,
   the PA becomes a watcher and the presence source becomes a PA.  The
   discussion in this document concentrates on the simple model; a
   presence source in text generally refers to the ultimate presence
   source: the entity that performs measurement.

                      +----------+    +----------+    +---------+
                      | Presence |    | Presence |____| Watcher |
                      |  Source  |    |  Agent   |    |         |
      +----------+    |    or    +----+    or    |    +---------+
      | Presence |____| Presence |    |  Watcher |
      |  Source  |    |  Agent   |    |          |
      +----------+    +----------+    +----------+




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           Figure 2: Iterative Application of the Logical Model


















































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4.  Problem Statement

   Continuous-valued data cannot always be treated in the same fashion
   as discrete-valued data.  This section outlines a number of
   considerations that distinguish continuous-valued data.  These
   considerations affect how the presence system uses continuous-valued
   data.

4.1.  Unguided Measurement

   A presence source is responsible for the measurement of presence
   data.  Unless the watcher is able to communicate preferences to the
   presence source, the process of measurement is unguided.

   In the event that a PA and watcher operate independently of the
   presence data source, there is a risk that continuous-valued data is
   measured inappropriately.  Values might be measured too frequently or
   with unneeded degree of accuracy, that is, accuracy is favoured too
   highly over cost.  Conversely, if cost is optimised, measurements
   might be insufficient in frequency or accuracy.

   Communicating watcher preferences to the presence source addresses
   this problem by making information about what the watcher wants
   available to the presence source.  With this information the
   measurement process is no longer unguided.

   Communicating watcher preferences to the presence source is
   especially critical if the watcher also incurs costs relating to the
   measuring of the continuous value.  The most direct cost is in time:
   the watcher might be forced to wait for measuring of information to
   an accuracy more stringent than needed.  However, it need not be
   limited to time.

4.2.  Presence Filters

   It is possible to resolve the problem of unguided measurement without
   resorting to explicit protocol mechanisms.  Presence filters
   [RFC4660] are able to convey much of a watcher's preferences to the
   PA.  If the PA has a means of communicating with a presence source,
   it is able to request measurement of continuous-valued data according
   to the preferences it is aware of.  By communicating the watcher's
   preferences in this manner, the presence source is able to measure
   accordingly.  Additional changes to presence subscriptions
   ([I-D.niemi-sipping-event-throttle]) and filter extensions
   ([I-D.ietf-geopriv-loc-filters]) make more information available to
   the PA; this information could be passed on.

   Figure 3 shows a simplified model of the existing system of filtering



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   for presence data.  The system assumes that presence information is
   perfect.  If this is not the case, the only option for a PA is to
   project the illusion that this is the case.  The only information
   available to the PA is to use the filter and throttling data
   available to it to limit the costs it incurs in retrieving
   information from sources.

      +--------------------------------------------------------+
      |    Presence Agent (PA)                                 |
      |                                                        |
      |         ,-----------------+<--------------+<--------------
      |        / (Presentity     /               /   SUBSCRIBE |
      |       |   Identifier)   /               /              |
      |       V                /               /               |
      |  ,----------.         |               |                |
      |  |          |         V               V                |
      |  | Presence |    \---------\     \----------\          |
      |  |  Master  |---->) Filter  )---->) Throttle )------------>
      |  |   Data   |    /---------/     /----------/   NOTIFY |
      |  |          |         |              /                 |
      |  `----------'         |,------------'                  |
      |    ^  ^  ^   ,-.      /                                |
      |    |  |  |  ( ? ) <--'            +----------+         |
      |    |   \  \  `-'                  | Internal |         |
      |    |    \  `----------------------| Presence |         |
      |    |     `.                       | Source   |         |
      |    |       `-.                    +----------+         |
      |    |          `.                                       |
      +----+------------+--------------------------------------+
           |             `.
           |               \
      +----------+    +----------+
      | Presence |    | Presence |
      |  Source  |    |  Source  |
      +----------+    +----------+

                      Figure 3: Presence Agent Model

4.3.  Quality

   Filters are not ideal indications of when and how to measure.  The
   purpose of a filter is to limit notifications to a watcher.  It is
   possible, in some cases to make an intelligent decision about how to
   take measurements based on filter; but filters can be misleading.  To
   re-purpose filters to the task of advising sources on how and when to
   measure can result in problems.

   In particular, a filter specification based on information quality



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   can be particularly misleading.  If a watcher specifies a filter that
   requests a particular quality, the dual purposes that filters are
   used for potentially conspire to degrade the service provided to the
   watcher.

      This is best illustrated with an example.  Suppose a watcher, Bob,
      is watching the location of a presentity, Alice.  Bob specifies a
      filter that specifies a maximum uncertainty of 50m.  If this is
      used to advise the presence source, the source attempts to
      determine a location within that uncertainty.  If the source is
      unable to meet the requirement, the filter ensures that no
      notification is sent to Bob. Bob could handle uncertainty of up to
      1000m if necessary.  However, if he specified a larger constraint,
      the source might use cheaper methods that never produce a result
      with the accuracy Bob really wants.  How does Bob specify that he
      wants uncertainty of 50m, but that he will settle for anything up
      to 1000m?

   From this example, it can be seen that "soft" quality preferences are
   useful where continuous-valued data is the subject.  These
   preferences are used to guide the measurement process, but aren't
   restrictive of the final result.

   Quality constraints can be used to ensure that cached data is not
   used.  For instance, a constraint might be placed on the timestamp
   that forces the measurement of new data.

   The hard, boolean nature of a filter is not tolerant of variation in
   quality.  Of course, it is possible to expand the goals of the filter
   document to include the requirements of this document.  The
   requirements here defined do not presume to exclude that possibility.

4.4.  Watcher Feedback

   A watcher requires adequate feedback from the PA about how its
   preferences are being acted upon.  To a watcher, a PA that fully
   communicates watcher preferences to a presence source, remains
   indistinguishable from a PA that is either less able to acquire data
   (because it relies on PUBLISH [RFC3903]), or simply chooses not to
   perform this communication.

   In some cases, a watcher is able to compensate for any limitations
   imposed by the PA.  As shown in Section 4.6.3 adaptive polling can be
   used to seek a particular value.  However, if a watcher uses polling
   for value-seeking, this potentially duplicates similar efforts from
   the PA or presence source.

   In other circumstances, shortcomings cannot be addressed by the



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   watcher.  For instance, perhaps the presence source is capable of
   providing information to a certain high degree of accuracy, but
   unless requested it does not do so (the cost is too high).  If the PA
   never requests highly accurate information, that information is never
   available to the watcher.  If filter documents are used as a medium
   for communicating watcher preferences, the watcher could set a filter
   that only selects highly accurate information, which could
   inadvertently suppress all notifications.

4.5.  Active and Passive Sources

   For a particular presence datum, the means by which the PA is able to
   acquire updated information varies.  For some forms of discrete-
   valued data--such as basic status--the PA might be considered
   absolutely authoritative, in that the information is absolutely
   correct by definition.  Data can be made available to the PA either
   passively or actively.

   Passive Acquisition:  The PA is a passive recipient of updated
      information with no means to trigger measurement.  SIP PUBLISH
      [RFC3903] is an example of how the PA could passively acquire
      data.

   Active Acquisition:  The PA is able to seek updated information, and
      does so based on one or more triggers.

   Providing the watcher information on the nature of a particular
   presence source is an important part of the feedback provided by the
   PA.  If the PA only passively acquires data, much of the
   considerations presented in this document become moot.  More
   significantly, if the PA does not provide any options to the watcher
   to influence its interactions with the presence source, the same
   applies.  Thus, it is when the PA provides some means of conveying
   watcher preferences to the presence source that active acquisition
   becomes useful.

      Back to Bob and Alice: This time, Bob wants to know when Alice
      passes by the library where Bob works.  Bob sets a filter,
      requesting that he only be notified when Alice passes within 100m
      of the library.  If the PA is passive, it could be that it never
      receives information when Alice passes by--the presence source
      might not publish the necessary information at the crucial moment.

4.6.  Triggering Measurement

   Stimulating the generation of a value for the continuous variable can
   be done through several methods:




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   o  immediate or on-demand triggers

   o  time-based or periodic triggers (polling)

   o  value-based triggers

4.6.1.  Immediate Triggering of Measurement

   An immediate request for measurement provides the simplest means of
   directly providing the presence source with necessary information.  A
   watcher makes a request to the PA, including its preferences.  The PA
   then acquires information from the presence source, passing watcher
   preferences directly to the source.

   For SIP presence, the means of communicating preferences available to
   a watcher is the SUBSCRIBE request.  This presents a challenge for
   the SIP presence framework if the presence source is not able to
   provide the requested information immediately.  RFC 3265 [RFC3265]
   states:

      When a SUBSCRIBE request is answered with a 200-class response,
      the notifier MUST immediately construct and send a NOTIFY request
      to the subscriber.

   If the PA is unable to provide an immediate notification due to lack
   of information, it must indicate this to the watcher.  A presence
   document might be a composit of continuous- and discrete-valued data.
   Any solution for continuous-valued data cannot affect the conveyance
   of discrete-valued data.  Compatibility with existing the existing
   presence framework is also desirable.  Therefore, an immediate
   notification is still necessary.

   Some time after the initial request, when the continuous-valued data
   becomes available, a second notification can be sent.  However,
   another conflict arises with event rate throttling.  When information
   becomes available, the notification might be suppressed due to a
   short elapsed time since the initial notification.

   Any means of triggering immediate measurement needs to consider these
   problems.

4.6.2.  Periodic Triggering of Measurement

   Periodic notifications of the value of presence data are not assumed
   to be necessary by the existing work.  Values are assumed to change
   infrequently, or if frequent changes are necessary, solutions have
   concentrated on means of throttling notifications.  RFC 3265
   [RFC3265] recommends that event packages specify a minimum interval



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   between notifications; and [I-D.niemi-sipping-event-throttle]
   provides a direct means of controlling this interval.

   If the watcher has an interest in the value of a particular datum
   over time, it is useful to be able to have the PA provide
   notifications at regular intervals.

   A similar time-based problem exists for periodic notification as did
   for the immediate request.  The PA cannot request presence
   information at the time that a notification is required--the presence
   source is unlikely to be able to produce a result so quickly.  The PA
   needs to allow the presence source sufficient time to make a
   measurement.  This time can be allocated before the notification is
   required so that all the necessary data is available for the
   notification.

   Deciding how much time to allow the presence source presents another
   problem.  Relying upon a value specified by the watcher ensures that
   the measurement process is guided appropriately.

4.6.3.  Value-based Triggering of Measurement

   A watcher might only be interested in a value if that value enters a
   particular range.  For instance, for location, the watcher might be
   interested when the presentity is in the vicinity of a particular
   landmark, or even the when two presentities approach each other.  A
   watcher that monitors the temperature of a presentity might be
   interested if the temperature exceeds a certain threshold.

   Value-seeking can be performed in different ways.  Given certain
   assumptions or knowledge about the rate of change of a value and the
   desired responsiveness, an adaptive polling method can be used.  The
   rate of polling can increase in frequency in proportion to the
   proximity of the current value to the target range.  In addition,
   time and quality constraints can be relaxed or made more stringent as
   appropriate.  The advantage of polling is that it can be performed
   with only a small amount of information; a PA or watcher is able to
   use polling for value-seeking.

   A presence source can potentially use alternative information to
   assist in value-seeking.  For data that is derived from other
   measurements, the value of the unprocessed measurements might provide
   an adequate indication of the value to obviate any need to continue
   measurement.  For instance, the set of wireless transmitters that can
   be observed by a wireless device can be used as a rough indication of
   location.





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5.  Requirements

   The requirements documented in this section relate to subscriptions
   for continuous-valued data.  These requirements do not make any
   assumptions about the nature of the relationship between PA and
   presence source.  A presence source is assumed to be present only to
   the extent that the measurement of a particular presence element
   affects the results observed by the watcher.

   A solution that addresses these requirements MAY address them based
   on a specific type of data.  Some requirements might not suit a
   generic solution.

5.1.  Quality Requirements

   Q1.  The system MUST provide a watcher the ability to express non-
        binding requirements on information quality for continuous-
        valued presence data.

        Motivation: Having a means to express preferences in non-binding
        fashion can have the desired effect in influencing the
        measurement process at the presence source without other side-
        effects.

   Q2.  The system MUST provide a means to indicate how information
        quality preferences are used or propagated.

        Motivation: Providing adequate feedback to a watcher assists the
        watcher in making decisions about its behaviour.  From the
        perspective of a PA, this requirement can only be fulfilled
        based on the knowledge it has available; it can know whether or
        not it is the presence source, but it cannot assume that the
        entity it requests information from is the ultimate source of
        the information.  Publishing information about the ultimate
        source of the data isn't necessary, but the watcher needs to
        know if its preferences are getting to that source.

        For instance, the PA or presence source might limit the extent
        to which quality parameters are able to bypass caches.

5.2.  Immediate Triggering Requirements

   I1.  The system MUST provide a means for a watcher to explicitly and
        immediately request measurement of a specified continuous-valued
        datum.

        Motivation: A direct request for data ensures that the presence
        source is properly advised of the constraints of a request.  It



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        also ensures that a watcher has access to updated information.

   I2.  The system MUST provide a means for the watcher to communicate
        time constraints on the measurement process.

        Motivation: Specifying time constraints ensures that the
        information is available to the watcher when required.  It also
        ensures that the presence source applies appropriate methods in
        measuring.

   I3.  The system MUST provide a means for a PA to limit support for
        immediate requests.

        Motivation: Making a direct request to the presence source
        increases the load on the presence source and PA.  A PA
        implementation might want to constrain access to immediate
        requests to prevent denial of service.

   I4.  The system MUST provide a means for a PA to indicate support for
        immediate requests, including any limits or constraints on that
        support.

        Motivation: Providing adequate feedback to the watcher ensures
        that the watcher is able to modify its behaviour accordingly.

5.3.  Periodic Triggering Requirements

   P1.  The system MUST provide a means to request periodic measurement
        of a continuous-valued datum at a specified interval.

        Motivation: Periodic measurement is the most basic means of
        enabling tracking of a value over time.  More sophisticated
        methods might be used, but this sets a minimum level of
        capability that can be exploited for any type of continuous-
        valued data.

   P2.  The system MUST provide a means for a PA to limit support for
        periodic requests.

        Motivation: Excessive polling rates might result in denial of
        service through excessive requests.

   P3.  The system MUST provide a means for a PA to indicate support for
        periodic measurement, including any limits or constraints.







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   P4.  The system MUST provide a means for a watcher to explicitly
        limit the rate of notifications.

        Motivation: Even without perfect information, the defining
        characteristic of continuous variables is the potential for
        continuous change.  This manifests in presence as a continuous
        stream of data from the PA to the watcher.  For a range of
        reasons--protection of network utilization not-withstanding--
        this is not desirable.

        References: [I-D.niemi-sipping-event-throttle]

5.4.  Value-Seeking Requirements

   V1.  The system MAY provide a means for a watcher to indicate a
        particular range of values to seek.

        Motivation: If a watcher is only interested in a certain range
        of values, limiting measurement and notification protects
        resources on both the presence source and watcher.

   V2.  The system MUST provide a means for a PA to indicate support for
        value-seeking requests, including any limits or constraints on
        that support.

        Motivation: Providing adequate feedback to the watcher ensures
        that the watcher is able to modify its behaviour accordingly.

5.5.  Timeliness Requirements

   T1.  Continuous-valued data MUST always have a timestamp that
        indicates when the value was measured.

        Motivation: A continuously varying datum is, by its nature,
        inevitably out of date at the time that the watcher receives it.
        In practice, this is only a problem if the time between
        measurement and receipt of the data is large.  Since this is a
        matter of degree, providing a timestamp ensures that a watcher
        is able to make a judgment about validity.

        If time information is not included, the recipient of
        continuous-valued information has no means of judging how
        current the information is.  PIDF [RFC3863] specifies a
        "timestamp" element, but this element is optional.  This
        requirement makes the value mandatory.

        The corollary to this that an item of continuous-valued data is
        automatically invalid if it is not timestamped.



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   T2.  The system MUST provide a watcher the ability to limit the age
        of data that it is provided.

        Motivation: This ensures that caching of data is only used to
        the extent that it is acceptable to the watcher.

        References: [I-D.thomson-geopriv-location-quality]

   T3.  The system MUST provide a means for a watcher to indicate how
        long measurement of continuous-valued data is allowed to take.

        Motivation: This indication assists the PA and presence source
        in making decisions about how much time to allocate to
        measurement; for periodic measurement, it provides a hint on
        when to start measurement.




































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6.  Security Considerations

   A number of requirements involve a PA making information about its
   operation available to a watcher.  This information might be consider
   sensitive by the operators of a PA.  Any solution that addresses
   these requirements MUST provide an option to suppress this
   information and MAY include guidance on when this might be
   appropriate.

   Many of the requirements in this document potentially result in PA
   behaviour being controlled to some extent by a watcher.  Due to the
   potential for increased load on the PA, a malicious watcher could
   attempt a denial of service attack by making repeated requests.  A
   periodic request or a request that includes value-seeking, in
   particular, require significant processing in order to service a
   relatively simple request.  Limiting the rate at which information is
   requested or generated can be used to mitigate this attack.  Any
   solution that addresses these requirements MUST consider the
   implications of denial of service on the PA.

   Caching of results can limit the load imposed by multiple requests
   for the same information.  To protect against denial of service, a PA
   MAY choose to suppress any options for bypassing cached data.




























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7.  Acknowledgements

   This document is a clumsy attempt to formalize the output of
   discussions on the nature of presence and its applicability to
   location information.  Adam Roach has been helpful in destroying
   misconceptions about presence, although this document might
   demonstrate that he wasn't entirely successful; any remaining
   misconceptions are entirely those of the author.  Thanks also to
   Richard Barnes, Robert Sparks, James Winterbottom.










































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8.  References

8.1.  Normative References

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

8.2.  Informative References

   [RFC2778]  Day, M., Rosenberg, J., and H. Sugano, "A Model for
              Presence and Instant Messaging", RFC 2778, February 2000.

   [RFC3265]  Roach, A., "Session Initiation Protocol (SIP)-Specific
              Event Notification", RFC 3265, June 2002.

   [RFC3693]  Cuellar, J., Morris, J., Mulligan, D., Peterson, J., and
              J. Polk, "Geopriv Requirements", RFC 3693, February 2004.

   [RFC3856]  Rosenberg, J., "A Presence Event Package for the Session
              Initiation Protocol (SIP)", RFC 3856, August 2004.

   [RFC3863]  Sugano, H., Fujimoto, S., Klyne, G., Bateman, A., Carr,
              W., and J. Peterson, "Presence Information Data Format
              (PIDF)", RFC 3863, August 2004.

   [RFC3903]  Niemi, A., "Session Initiation Protocol (SIP) Extension
              for Event State Publication", RFC 3903, October 2004.

   [RFC4079]  Peterson, J., "A Presence Architecture for the
              Distribution of GEOPRIV Location Objects", RFC 4079,
              July 2005.

   [RFC4119]  Peterson, J., "A Presence-based GEOPRIV Location Object
              Format", RFC 4119, December 2005.

   [RFC4480]  Schulzrinne, H., Gurbani, V., Kyzivat, P., and J.
              Rosenberg, "RPID: Rich Presence Extensions to the Presence
              Information Data Format (PIDF)", RFC 4480, July 2006.

   [RFC4660]  Khartabil, H., Leppanen, E., Lonnfors, M., and J. Costa-
              Requena, "Functional Description of Event Notification
              Filtering", RFC 4660, September 2006.

   [I-D.ietf-geopriv-lbyr-requirements]
              Marshall, R., "Requirements for a Location-by-Reference
              Mechanism", draft-ietf-geopriv-lbyr-requirements-03 (work
              in progress), July 2008.




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   [I-D.ietf-geopriv-loc-filters]
              Mahy, R. and B. Rosen, "A Document Format for Filtering
              and Reporting Location Notications in the  Presence
              Information Document Format Location Object (PIDF-LO)",
              draft-ietf-geopriv-loc-filters-02 (work in progress),
              July 2008.

   [I-D.barnes-geopriv-lo-sec]
              Barnes, R., Lepinski, M., Tschofenig, H., and H.
              Schulzrinne, "Additional Location Privacy Considerations",
              draft-barnes-geopriv-lo-sec-03 (work in progress),
              July 2008.

   [I-D.garcia-simple-indirect-presence-publish]
              Garcia-Martin, M., Tschofenig, H., and H. Schulzrinne,
              "Indirect Presence Publication with the Session Initiation
              Protocol(SIP)",
              draft-garcia-simple-indirect-presence-publish-00 (work in
              progress), February 2008.

   [I-D.niemi-sipping-event-throttle]
              Niemi, A., Kiss, K., and S. Loreto, "Session Initiation
              Protocol (SIP) Event Notification Extension for
              Notification Throttling",
              draft-niemi-sipping-event-throttle-07 (work in progress),
              October 2008.

   [I-D.thomson-geopriv-uncertainty]
              Thomson, M. and J. Winterbottom, "Representation of
              Uncertainty and Confidence in PIDF-LO",
              draft-thomson-geopriv-uncertainty-01 (work in progress),
              June 2008.

   [I-D.thomson-geopriv-location-quality]
              Thomson, M. and J. Winterbottom, "Specifying Location
              Quality Constraints in Location Protocols",
              draft-thomson-geopriv-location-quality-01 (work in
              progress), May 2008.

   [ISO.GUM]  ISO/IEC, "Guide to the expression of uncertainty in
              measurement (GUM)", Guide 98:1995, 1995.










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Appendix A.  Presence Agent and Source Interactions

   [[Ed: this section has some informational value, but need to
   determine how much that contributes to the document.]]

   This document specifies requirements that expose the nature of the
   association between PA and presence source.  While there are no
   direct requirements on this interface and proprietary solutions are
   entirely appropriate, it is hoped that these requirements will
   influence the design of any protocol mechanisms used on this
   interface.

   Associations between PA and presence sources could be largely static
   in nature, as is true of the methods described in [RFC3856].
   Establishing dynamic associations between PA and presence source is
   an option where disparate presence sources are required.  This is
   especially true for location information, where close physical
   proximity between presentity and source is usually required;
   consequently the presence source can dynamically change as the
   presentity moves.

   Location by-reference [I-D.ietf-geopriv-lbyr-requirements] provides a
   means whereby a relationship between any entity and the Location
   Generator can be established.  By contacting the Location Generator,
   a requester is able to specify preferences for how location
   information is generated/measured.  A location reference forms the
   basis for establishing an association between Location Generator and
   a Location Server.

   For presence, Indirect publish
   [I-D.garcia-simple-indirect-presence-publish] describes how a PA is
   able to use the indirection provided by a URI.  The URI is used to
   establish a link between the generator of presence information and
   the PA.  The URI is distinguished by two characteristics:

   o  the host serving the URI is the presence source

   o  additional information in the URI provides enough information to
      uniquely identify the presentity to the presence source












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Author's Address

   Martin Thomson
   Andrew
   PO Box U40
   Wollongong University Campus, NSW  2500
   AU

   Phone: +61 2 4221 2915
   Email: martin.thomson@andrew.com
   URI:   http://www.andrew.com/








































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Full Copyright Statement

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