WG Working Group                                                N. Davis
Internet-Draft                                                     Ciena
Intended status: Informational                           24 October 2022
Expires: 27 April 2023


                          Modelling Boundaries
               draft-davis-netmod-modelling-boundaries-00

Abstract

   Current modelling techniques appear to have boundaries that make
   representation of some concepts in modern problems, such as intent
   and capability, challenging.  The concepts all have in common the
   need to represent uncertainty and vagueness.  The challenge results
   from the rigidity of boundary representation, including the
   absoluteness of instance value and the process of classification
   itself, provided by current techniques.

   When describing solutions, a softer approach seems necessary where
   the emphasis is on the focus of a particular thing.  Intelligent
   control (use of AI/ML etc.) could take advantage of partial
   compatibilities etc. if a softer representation was achieved.

   The solution representation appears to require

   *  Expression of range, preference and focus as a fundamental part of
      the metamodel

   *  Recursive tightening of constraints as a native approach of the
      modeling technique

   This lead to need to enhance the metamodel of languages that define
   properties.  It appears that the enhancement could be within, as
   extensions to, and compatible with current definitions.
   YANG is a language used to define properties and it appears that YANG
   is appropriately formed to accommodate such extensions.

About This Document

   This note is to be removed before publishing as an RFC.

   The latest revision of this draft can be found at
   https://example.com/LATEST.  Status information for this document may
   be found at https://datatracker.ietf.org/doc/draft-davis-netmod-
   modelling-boundaries/.





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Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   4
     1.1.  Observation: Terminology  . . . . . . . . . . . . . . . .   5
   2.  Conventions and Definitions . . . . . . . . . . . . . . . . .   5
   3.  Analysis  . . . . . . . . . . . . . . . . . . . . . . . . . .   5
     3.1.  Specific challenge areas - some terminology . . . . . . .   5
       3.1.1.  Specification of *Expectation* and *Intention*  . . .   6
       3.1.2.  Specification of *Capability* . . . . . . . . . . . .   6
       3.1.3.  Expression of *Partial Visibility* (of state etc.)  .   7



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     3.2.  Observation: Progressive Narrowing of definition  . . . .   7
     3.3.  Observation: Definition expansion . . . . . . . . . . . .   8
     3.4.  Observation: Expression of capabilities . . . . . . . . .   9
     3.5.  Observation: Application of expression of capability  . .   9
     3.6.  Observation: Compatibility  . . . . . . . . . . . . . . .  10
     3.7.  Observation: Defining the boundary  . . . . . . . . . . .  11
     3.8.  Exploration: The nature of the solution . . . . . . . . .  12
     3.9.  Clarification: Complex/Blurry/Fuzzy boundaries in the
            solution . . . . . . . . . . . . . . . . . . . . . . . .  13
     3.10. Observation: Artificial Intelligence and uncertainty  . .  14
     3.11. Observation: No longer instance config, everything is
            expectation-intention  . . . . . . . . . . . . . . . . .  15
     3.12. Observation: Intention-Expectation interaction  . . . . .  16
     3.13. Observation: Instance state . . . . . . . . . . . . . . .  17
     3.14. Observation: Foldaway complexity  . . . . . . . . . . . .  17
     3.15. Exploration: Focusses, boundaries and partial
            descriptions . . . . . . . . . . . . . . . . . . . . . .  19
     3.16. Observation: Two distinct perspectives and viewpoints . .  20
     3.17. Observation: Capability in more detail  . . . . . . . . .  22
     3.18. Observation: Occurrence . . . . . . . . . . . . . . . . .  22
     3.19. Observation: One model  . . . . . . . . . . . . . . . . .  23
     3.20. Observation: Partially satisfied request  . . . . . . . .  24
     3.21. Observation: Other solution elements that benefit . . . .  25
     3.22. Observation: Outcome and Experience . . . . . . . . . . .  25
     3.23. Observation: Metamodel v Model  . . . . . . . . . . . . .  26
   4.  Solution: Formulation . . . . . . . . . . . . . . . . . . . .  26
     4.1.  Solution: Methodology . . . . . . . . . . . . . . . . . .  27
     4.2.  Solution: Considering the property  . . . . . . . . . . .  27
     4.3.  Solution: Occurrence Specification  . . . . . . . . . . .  28
     4.4.  Observation: Uniformity of expression . . . . . . . . . .  28
     4.5.  Solution: Tooling support . . . . . . . . . . . . . . . .  28
   5.  Target and next steps . . . . . . . . . . . . . . . . . . . .  28
   6.  Conclusion  . . . . . . . . . . . . . . . . . . . . . . . . .  29
   7.  Security Considerations . . . . . . . . . . . . . . . . . . .  30
   8.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .  30
   9.  Informative References  . . . . . . . . . . . . . . . . . . .  30
   10. Normative References  . . . . . . . . . . . . . . . . . . . .  30
   Appendix A.  Appendix A - Problem/Solution Examples . . . . . . .  31
   Appendix B.  Appendix B - Sketch of an enhanced YANG form . . . .  31
     B.1.  Progression . . . . . . . . . . . . . . . . . . . . . . .  32
     B.2.  Language  . . . . . . . . . . . . . . . . . . . . . . . .  32
     B.3.  Key concepts  . . . . . . . . . . . . . . . . . . . . . .  33
     B.4.  Observation . . . . . . . . . . . . . . . . . . . . . . .  33
     B.5.  Progressing to the language . . . . . . . . . . . . . . .  34
     B.6.  JSONized YANG . . . . . . . . . . . . . . . . . . . . . .  34
       B.6.1.  JSONised Header . . . . . . . . . . . . . . . . . . .  34
       B.6.2.  JSONized body . . . . . . . . . . . . . . . . . . . .  36
     B.7.  Schema for the schema . . . . . . . . . . . . . . . . . .  38



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     B.8.  An example of spec occurrence and rules . . . . . . . . .  45
       B.8.1.  Rough notes . . . . . . . . . . . . . . . . . . . . .  45
     B.9.  The current schema  . . . . . . . . . . . . . . . . . . .  46
     B.10. YANG tree . . . . . . . . . . . . . . . . . . . . . . . .  46
     B.11. Instance example  . . . . . . . . . . . . . . . . . . . .  46
     B.12. The extended schema . . . . . . . . . . . . . . . . . . .  46
     B.13. Versioning considerations . . . . . . . . . . . . . . . .  46
   Appendix C.  Appendix C - My ref / your ref . . . . . . . . . . .  46
   Appendix D.  Appendix D - Occurrence  . . . . . . . . . . . . . .  46
   Appendix E.  Appendix E - Narrowing, splitting and merging  . . .  48
     E.1.  Narrowing . . . . . . . . . . . . . . . . . . . . . . . .  48
     E.2.  Splitting . . . . . . . . . . . . . . . . . . . . . . . .  50
     E.3.  Merging . . . . . . . . . . . . . . . . . . . . . . . . .  50
   Appendix F.  Appendix F - A traffic example . . . . . . . . . . .  51
   Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . .  51
   Contributors  . . . . . . . . . . . . . . . . . . . . . . . . . .  51
   Author's Address  . . . . . . . . . . . . . . . . . . . . . . . .  51

1.  Introduction

   The essential challenge being considered in this paper is that of
   statement of partially constrained definition of a thing (property,
   collection of properties, entity, collection of entities etc.) and of
   progression through stages of refinement of constraints leading
   eventually potentially to precise single value forms of refinements
   of that thing.

   The constrained definition of a thing requires the expression of a
   boundary that surrounds all allowed/possible values for that thing.

   The paper will introduce the term "Occurrence" and explain that
   through the progression, a single occurrence gives rise to multiple
   occurrences at the next stage of refinement and that this expansion
   repeats from one stage to the next.

   It appears that many aspects of the industries' problems/solutions
   require such a progression of gradual refinement and hence statement
   of partial constraint and occurrence.  However, it seems that current
   languages do not readily accommodate the necessary structures.  It is
   possible to use existing languages, but the realization seems clumsy
   and bolted on as opposed to inherent to the language.










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   Considering the apparent prevalence of need for expression of ranges
   and uncertainty, it seems strange that there should be no readily
   available language, so part of the purpose of this paper is to
   stimulate discussion to help find an appropriate existing language.
   If, as appears to be the case, there is no well-suited language, then
   the next obvious step is to consider extension of YANG so that it can
   accommodate the need.

   This paper works through an analysis expressed via threads of
   observation and exploration that are then woven together to form the
   fabric of the problem and solution.

   In an appendix, a sketch of a YANG form of solution is set out to
   assist in the understanding of the problem.  It is anticipated that
   the YANG form will seed advancements to the YANG language in this
   area.

1.1.  Observation: Terminology

   We all recognize the challenge with any terminology.  Terms are for
   communication convenience (they are not fundamental).  Unfortunately,
   each term comes with baggage and each of us has a different
   understanding of each term.  Sometimes these differences are subtle,
   but sometimes a term spreads across a very wide space.

   Each key term used in this document has specific local meaning which
   the authors attempt to clarify.  However, it is probable that the
   definitions here are too vague to ensure full shared understanding.
   Ongoing work will be required.

2.  Conventions and Definitions

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   "SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and
   "OPTIONAL" in this document are to be interpreted as described in
   BCP 14 [RFC2119] [RFC8174] when, and only when, they appear in all
   capitals, as shown here.

3.  Analysis

   The following section introduces concepts and associated terminology
   and gradually assembles a picture of the needs.

3.1.  Specific challenge areas - some terminology

   Each of the following require, for any property, expression of range,
   preference, uncertainty, interdependency etc.  The specific
   challenges will be discussed in following sections.



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   The solution to the problem appears to need a language that supports
   expression narrowing of definition such that that language can be
   applied recursively to form a progression of increasingly narrowed
   definitions from the very broad to the very specific.

3.1.1.  Specification of *Expectation* and *Intention*

   Specification of Expectation/Intention is a statement of desired
   outcome/experience in terms of constraints which includes statement
   of preference and acceptable value ranges etc.

   This has resulted from some negotiation (or imposition) where, in a
   simple case, a client and provider have formed an agreement and where
   the client has an Expectation that the agreement will be fulfilled,
   and the provider has an Intention to fulfil the agreement.

   The expression of outcome/experience is as viewed from the outside of
   the provider solution, i.e., what is exposed by the provider.

   Intention is a sub-case of "Specification of *Capability*" (and
   expectation is a sub-case of "Specification of *Need*" - note that
   "Need" is not covered in detail in this document).

   Related terms

   *  intent

   *  service

3.1.2.  Specification of *Capability*

   This is a statement of opportunity for behaviour to be exhibited
   which includes statement of possible ranges and interdependencies
   etc.

   The expression of capability of a provider system, presented as that
   of an opaque component, results from consideration, by the provider,
   of various potential assemblies of their internal capabilities (e.g.,
   can be considered as a recursion of systems of components), governed
   by their business purpose etc.

   It is becoming increasingly apparent that there is a need for a
   machine interpretable expression of capability and hence a language
   for such expression.

   Most recently, specific cases of need have been identified as
   automation solutions in the following areas mature:




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   *  Advertising capability (both at a commercial boundary and for
      components in a solution)

   *  Negotiation towards contract (where capability requirement and
      offer are refined)

   *  Planning infrastructure buildout (where capability of solution and
      of components is required)

   *  Intent solution formation (intent is the result of negotiation,
      expressing solution capability)

   *  Any situation where specialized components need to be assembled

3.1.3.  Expression of *Partial Visibility* (of state etc.)

   Any real environment will suffer imprecision, loss and disruption.
   Any statement made about properties (behaviour, characteristics,
   etc.) of things in that environment may not be fully available
   (temporarily due to some impairment or permanently due to cost/
   complexity (the measure is an approximation as it is not practical to
   measure precisely)).

   This leads to the need, for any property, to be able to state
   absence, probability, uncertainty and vagueness (varying over the
   lifecycle etc. as will be discussed later).

3.2.  Observation: Progressive Narrowing of definition

   Traditional modeling tends to lead to a class model (potentially with
   inheritance), which provides precise definitions of properties etc.
   (current YANG models are of this form), where each class is realized
   as instances in the solution and where each instance provides a
   precise value for each property defined as mandatory in the class
   etc.

   However, what actually appears to happen in many areas of the
   solution is a process of gradual narrowing of definition where that
   narrowing takes place in a progression of discrete steps.

   Consider the following rough example progression (stages may be
   omitted/repeated):

   *  A version of a standard may provide a definition of technology
      capability.






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   *  A vendor solution may have a narrower capability than the
      standard, perhaps due to a target price point etc.  A vendor may
      have several solutions, each with a different narrowing

   *  An application of the vendor solution may have a further narrowing
      of capability, perhaps due to some combinatorial effect in the
      deployment

   *  The use of a vendor capability at a particular point in a
      structure of a solution may have a further narrowing of capability
      as a result of need or policy at that point

   *  At a particular point in a structure of a solution under
      particular circumstances there may be an even narrower allowed
      capability, for example under certain environmental conditions the
      thermal considerations may require the solution to run at low
      power etc.

   *  Proof of concept (PoC) of the solution may have an even narrower
      allowed capability

   *  An example diagram related to a single use case for a PoC may
      require an extremely narrow definition

   *  Where there is delegated control, even the fully refined
      "instance", perhaps in the single use case for the PoC mentioned
      above, may be specified in terms of constrained definition as
      opposed to absolute value.

   *  Etc.

   Traditional Classification and statement of instance specification do
   not deal with the above.  Some constraint mechanisms deal with the
   above in part, but these are often an afterthought, are clumsy and
   have significant shortfalls as will be illustrated.

3.3.  Observation: Definition expansion

   In addition to the recursive reduction discussed above at each level
   definition may be introduced that did not appear in the previous
   stage as a result of capability from the intersection with a separate
   narrowing.  For example, the vendor solution may extend with
   proprietary features not defined in the standard

   Further, there will be evolution and growth so the next development
   of the standard etc. may extend/adjust the statements.





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   Of course, any definition introduced at any point in the progression
   can be narrowed at the next stage of the progression.

   The ultimate progression is an intertwining of expansion and
   reduction stages.

3.4.  Observation: Expression of capabilities

   For any control solution component at any stage of the above
   intertwined progression, it is necessary to understand the capability
   and indeed some of the progression.

   This requires runtime interpretation of expression, in normalized
   uniform machine interpretable form, of the capabilities (properties
   and constraints) exposed by the relevant assembly.

   Traditional classification is too blunt a tool for this purpose as
   will be illustrated.

3.5.  Observation: Application of expression of capability

   In a control system context, capability expression applies to:

   *  the controlled system with respect to the exposed model and
      allowed activities

   *  the control system and its exposed capabilities (both the control
      provider and control client)

   Each of the above:

   *  is always an abstraction/view of the underling real system

   *  applies for any interaction at any boundary

   The above may have further depth such, for example:

   *  the controlled system exposure can be controlled and adjusted

   *  the control system exposure can be controlled and adjusted

   *  etc.

   The capability descriptions need to detail all deterministic per case
   variations (not just a broad- brush statement on the model versions
   supported).





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3.6.  Observation: Compatibility

   The following applies to any interacting entities with respect to any
   aspect of interaction (e.g., a control system component interacting
   with another control system component about things that are
   controlled).

   Note that here a component is a conceptual functional construct that
   has ports through which it can communicate with other components and
   that encapsulates some functional capability.  Generalized component
   is described in [ONF TR-512.A.2]

   Two components are suitably compatible and can interact with respect
   to a particular application so long as their exposed capabilities
   have an appropriate/sufficient intersection.

   Interaction between Semi-Compatible Entities is possible where:

   *  Semantic intersection enables a subset of capabilities (resulting
      in a meaningful capability set).

   *  Partially mappable expression provides sufficient meaning (some
      mappings may be approximate and partially ambiguous, but only in
      areas where the this is not overly relevant)

   The result of the intersection is usually a narrower statement of
   capability than the statement for the two components (it most it can
   be the full statement).  In some cases, the intersection may be the
   empty set and hence there can be no interaction opportunity.

   *  Where a feature is preferred but not mandatory, the empty set
      intersection is acceptable

   *  Very few properties are fundamentally mandatory, importance is
      dependent upon specific application and specific interaction
      within that application.

   For any interaction between two components A and B compatibility is
   determined by the intersection of:

   *  application interaction semantic

   *  interface transfer capability

   *  component A capabilities/needs

   *  component B capabilities/needs




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   If any of the mandatory application interaction semantic elements are
   eliminated, then the interaction cannot be supported.  If preferred
   or optional semantic elements are eliminated, then the interaction
   can be supported at some degree of degraded capability.

   Note that this discussion fragment focusses on the direct interaction
   and not on the implications for other interactions etc.

   Compatibility must be considered over the intertwined lifecycles of
   the interacting components as each independently evolves in terms of
   both functional capability and interface expression.  This also
   includes migration of boundaries.

3.7.  Observation: Defining the boundary

   The general problem identified is the representation of a semantic
   space by defining its boundary.  Clearly, the boundary is itself
   defined in terms of ranges, however, the boundary is not necessarily
   defined with absolute range values, and it is not necessarily fixed
   in time.

   The boundary may, for example,:

   *  change, in position and in precision, through the lifecycle of the
      thing (as it matures... where it tends to become tighter)

   *  be interdependent with other boundaries

   *  have uncertainty in position of boundary and/or limited interest
      in positioning of boundary (don't know, somewhere round about
      here, don't care, that's precise enough)

   *  also have specification (and measurement) of acceptable, degraded
      and unacceptable positioning (there is also a need to indicate
      other aspects, e.g., for how long a particular degradation is
      acceptable or what the degradation costs etc.)

   *  changes of positioning and precision over time or over stages of
      lifecycle

   *  have associated probability (likelihood of a particular
      positioning) and preference (for a particular position)

   The above considerations apply similarly to intent specification,
   capability specification and partial visibility.






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   The same challenges also appear in planning and in negotiation where
   there is a need to state vaguely understood and interdependent
   properties etc.

   Considering lifecycle stages, a property defining a boundary of a
   thing, e.g., the property acceptable temperature range, may have one
   defined range at one part of the lifecycle and another defined range
   at another part of the lifecycle where this variation is known at the
   time of specification such that the specification needs to include
   this lifecycle aspect.

   The variation may be temporal or may be dependent upon some other
   variable property.

3.8.  Exploration: The nature of the solution

   Considering the observations and other considerations above, the
   solution requires support for a property to

   *  Be stated in terms of ranges with focusses and complex
      (potentially fuzzy) boundaries where that statement defines a
      semantic volume and where the boundary may not be sharp

   *  Have statements that interrelate it with another property (or
      properties)

   *  Have multiple boundary preference levels and/or probability levels
      where the preference/importance level is per interaction and not
      an aspect of fundamental property definition

   *  Be defined in terms of a narrowing of a previously expressed
      volume (i.e., a further narrowing) where a single point value is a
      very narrow range (many single values are actually abstractions of
      complex ranges, e.g. 2Mbit/s is +/-15ppm)

   *  Be defined in such a way that simple property definitions are not
      burdened by the structures that enable sophisticated definition
      (i.e., the expression should be such that the complexity of
      expression "folds away" for simple statements)

   *  Use a representation where there is no distinction in expression
      opportunity between a statement of capability definition, intent
      definition, actual value etc. such that all expressions are of the
      same essential form







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   This is a fundamental change in the nature of the solution... a
   change in paradigm and metamodel where the properties are defined by
   complex/fuzzy bounded/focused spaces related to other complex/fuzzy
   bounded/focused spaces with preferred/probable positions etc.

3.9.  Clarification: Complex/Blurry/Fuzzy boundaries in the solution

   To illustrate the complex/fuzzy boundaries, partial compatibility and
   several other aspects, an example of color usage is helpful.  Whilst
   color may not be the most important aspect of the solution in key
   industries related to this work, it is an easy example to understand.
   It is suggested here that the same challenge applies to ALL
   properties at least to some relevant degree.

   Consider a request for a physical item that has a color where the
   requestor, whilst interested in the color is not overly concerned.

   Their request for the item may include an expectation on color where
   that expectation is that the choice of color is not a showstopper but
   there is a preference for red and if not red then green.  The request
   does not need to include the color and if not included a choice will
   be made by the provider on some basis outside the interaction.

   The provider may not know what red is but may know green and have the
   item in green which will be appreciated by the client.

   Even if the provider does not have green any color will do.  In fact,
   the provider, in its response, need not even say what the color
   actually is!

   However, if the client indicates that the item provided must not be
   pink, then unless the provider knows what pink is, it cannot satisfy
   the request and the boundary now has a hard edge, so an aspect of the
   request is now mandatory.

   In this case, assuming the provider does know what pink is, the
   provider could respond with "the color is not pink" but provide no
   more details.

   In the example above the definition of color was complex/fuzzy to
   some degree, the providers understanding of pink may not match the
   client's exactly and the definition if the boundary between pink and
   red may be unclear and vary from occasion to occasion.








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   The color was specified by the client using colors by name as
   enumerated literals.  Now consider that the provider understand color
   in RGB.  It is possible that the color Red is not just 255,0,0, but
   is actually a range of colors in a volume bounded on the red scale by
   255 at one extreme and 240 at the other.  Further, red is a complex
   volume including on its boundary 255,10,10 and 250,8,8 etc.

   Now when the client asks for red, the provider can select color in
   the range defined.

   But it may also be the case that the color is not perfect so that
   there is always a little green and blue somewhere between 2 and 3 on
   both scales and the red coloration process is inaccurate so that the
   color produced is somewhere between 253 and 250.

   Further the color fades a little over time and in some lights looks a
   little more bluish.  These factors may need to be taken into account
   (as interactions between properties) if the request is for red and
   the duration of use is to be 10 years where the usage will be in
   various different lights.

   So, the request for red must be qualified by the above.  In a
   negotiation the requestor may even have broadened their view of red
   to include some maroon shades in their preference for Red, so that
   may now be a list of similar colors etc.

   The example above illustrates the need for the opportunity to specify
   range and interrelationship as a fundamental aspect of specification
   of color.  The color attribute needs the opportunity to deal with the
   above within its scope, not as a pile of arbitrary other properties.

   On the measurement side, it may not be possible to distinguish
   between anything within a range of 255 and 252 red etc. and further
   if the light level is low the color measurement may dither etc.

   In general, when a specific value is specified, e.g., "A" must equal
   5, this equates to a fuzzy setting that has hard boundaries.

   It is argued here that the above consideration applies to all
   properties.

3.10.  Observation: Artificial Intelligence and uncertainty

   As the spread of system automation progresses, the problem becomes
   increasingly complex.  This leads to the necessary expansion of use
   of AI/ML techniques in the solution.





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   These techniques deal well with uncertainty, approximation and
   fuzziness unlike traditional systems that tend to only work as
   precise coded solutions and absolute values with the occasional
   specific hack to deal with ranges and approximation.

   AI/ML solutions would benefit from the opportunity to express range,
   uncertainty etc. in any/all values/structures and to see uncertainty
   in all inputs.  Considering that the problem space is one of range,
   preference, approximation as discussed, it seems fundamentally
   necessary to expand the opportunity for expression as discussed in
   this document.

3.11.  Observation: No longer instance config, everything is
       expectation-intention

   The idea of Expectation/Intention as discussed earlier can be further
   developed.  Consider an example where a client has an expectation
   that the integer property "A" (perhaps a temperature of an "oven"
   containing a component that needs to operate within a particular
   range) is to take a value between 5 and 10 (with some unit, e.g.,
   Celsius.  It is OK to leave the units open when there are no specific
   values, but once values are being expressed, the units MUST be
   provided) . The provider could have the intention to make A take the
   value between 5 and 10 as requested, but to achieve this a complex
   process needs to be performed so it will take time to achieve a value
   in the range and there is some progression that needs to be reported.

   Eventually the provider achieves a value in the target range, but it
   is unable to state the value precisely as there is high-rate jitter
   and hence it can report that the value is between 6 and 9.

   The above example reflects the need to be able to state and report
   ranges for a property.

   Now consider the case where the system is more precise.  The client
   requires and has the expectation for A to take the value 5 (which is
   simply a very narrow range from 5 to 5) and the provider has the
   intention to achieve this, but again this will take time.  The
   provider reports progress towards 5 and eventually reports that 5 has
   been achieved.

   The above example reflects the need to be able report convergence on
   a property value even where the value is simple.  In general, the
   client may want to state a maximum time allowed to achieve any
   specific outcome and/or the provider may want to state a predicted
   time for any specific interaction.





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   Finally consider a case where the system has greater performance.
   The client requires and has the expectation for A to take the value 5
   and the provider the intention to achieve this.  The value can be
   achieved immediately, so the provider can simply report this back
   directly.  In this case the provider would predict an effective delay
   of 0 seconds (which can be implied as the value is returned
   immediately).

   The final case could be viewed as a SET the property of an instance
   of a class and hence special, but it is no less of an intent-
   expectation case than any of the others.  Indeed, it is possible that
   for a particular specific intent-expectation, on some occasions the
   achievement is immediate and on others it takes a while and for some
   parts of the range of possible settings the value is precise, but for
   other parts it is a range (perhaps at the extreme ends of operation).

   Clearly, it is highly beneficial (and even arguably, necessary) to
   have one uniform representation that caters for all cases.  Ideally,
   this method would appear as light as a SET where the value is precise
   and the achievement is immediate but would deal with the
   sophistication required where the value is a range, the result is a
   sub-range, and it takes time to achieve the result.

   Assuming that such a representation is achieved, then a traditional
   "instance specification" is actually sub-case of intention/
   achievement (or "intent" as defined by rough common usage) and hence
   not something distinct.  Indeed, the notion is that an instance is
   simply an occurrence at the most extreme narrowing, the lowest and
   most detailed available view, of definition and as noted above, this
   lowest available (visible) view of a realization may not be precise.
   There are always many details "below" this "lowest available visible
   view" that are not exposed.

   Any expectation/intention statement expression may have a mix of
   degrees of tightness of statement from vague to single value (and
   hence suitable to use for all cases of "instance specification") and
   allow representation of a mix of ranges and of single values.

3.12.  Observation: Intention-Expectation interaction

   Clearly, a solution does not operate on a single requirement in
   isolation, there may be multiple agreements and hence multiple
   Intention-Expectations competing for the solution resources.  Within
   the expression of each Intention-Expectation there is a need to state
   importance and this will interact with preemption policy.






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3.13.  Observation: Instance state

   As discussed above, an instance is an occurrence at the lowest and
   most detailed available view at the extreme end of the narrowing.  In
   addition to state related to progression of achievement of
   expectation/intention (traditional "config"), there is also state
   related to monitored/measured properties of the solution (not
   directly related to config).

   These properties are derived from monitoring devices that perform
   some processing of events within the solution.  The events are
   detected by a detector.  Very few of all of the possible event
   sources are monitored by detectors.

   All detectors are ultimately imprecise and may fail to operate.  The
   information from a detector may be temporarily unavailable, delayed,
   degraded etc.

   The representation of the simple detected value should include
   qualifications related to its quality etc.

   A machine interpretable specification of capability for the property
   should provide details of its derivation from other less abstracted
   properties.  For example, there may be a property that is detected
   where the detections are counted over some period and compared with a
   threshold
   where the crossing of that threshold is reflected by another property
   that is itself counted and compared with another threshold that if
   crossed changes the state of the property of concern.  An example of
   a property resulting from this pattern is the Severely Error Second
   alert.

   Understanding this pattern and other related patterns would enable a
   control solution to interpret the relationship between the various
   properties (currently, at best, solutions are explicitly coded to
   deal with properties with human oriented similarities).

3.14.  Observation: Foldaway complexity

   It was noted in an earlier section that "Ideally, this method would
   appear as light ... where the value is precise and the achievement is
   immediate but would deal with the sophistication required where the
   value is a range, the result is a sub-range, and it takes time to
   achieve the result.".







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   In general, it is highly desirable for the representation of common
   and simple cases to look/be simple and not be burdened by the more
   sophisticated structures that allow for more complex cases.  Ideally
   the representation has "foldaway complexity".

   An analogy can be drawn with human language grammar where the
   structure that allows sophisticated speech is not visible in simple
   speech.

   Several sketches (in rough JSON) of a configuration statement for a
   property "temperature" follow.

   Basic:

     "temperature":"5",

   More versatile:

     "temperature":{

           "acceptable-range":"5-12",

           "preferred-range":"7-9"

     }

   More sophisticated:

     "temperature":{

           "acceptable-range":"5-12",

           "preferred-range":"7-9",

           "upper-warn-threshold":"11",

           "lower-warn-threshold":"6",

           "Fail-alarm"{

                 "less-than":"5",

                 "greater-than":"12"

           }

     }




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   In this example the schema for:

     "temperature":{

           "acceptable-range":"5-12",

           "preferred-range":"7-9"

     }

   would identify preferred-range as optional, would identify
   "acceptable-range" as mandatory and the primary property and would
   identify the foldaway nature if only one value is provided in the
   range:

     "temperature":"6"

   is conformant with the schema.

   In addition, in a simple case a subset schema could be designed that
   was compatible with the main schema that only allowed the single
   value temperature.

   Ideally, considering the common requirements across all properties,
   the terms used in the schema nested within the property name would be
   standard terms etc.

3.15.  Exploration: Focusses, boundaries and partial descriptions

   Considering the progressive narrowing of boundaries, it is possible
   to consider anything as represented by a fully capable generalized
   thing with constraints (everything is a focused thing).  It is also
   possible to consider a subset of things where the focus is thing with
   ports.  Not all things have ports.  A thing with one or more ports
   can be called a component.  The component is a thing which has ports.
   Anything that has ports is a component.  The boundary around this
   focus is the presence of ports.

   A physical thing is a thing that can be measured with a ruler.  Some,
   but not all, things that are physical that can be measured with a
   ruler have ports.

   A functional thing is a thing that has behavior.  A functional thing
   is not physical, although it must be realized eventually by physical
   things.  Functional things have ports, as this is where the behavior
   is exposed (although they need not be represented).





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   So, there is a set of physical things disjoint from a set of
   functional things and a set of components that has an intersection
   with both the physical thing set and the functional thing set where
   the functional thing set is a subset of the component set.

   Anything that has ports is a component (as per the component-system
   patter described in [ONF TR-512.A.2]).  Many components will not yet
   be known etc., but the semantic of "component" remains unchanged when
   they are exposed.  As not all components are known, not all
   properties that can apply to components are known.  Adding properties
   does not change the semantics of "component", but it does improve the
   clarity.

   The progression above is essentially, specialization by narrowing of
   focus.  The broadest "Thing" has all possible characteristics and
   capabilities.  Specific semantics relate to the model of a specific
   thing where that is the narrowing of the broadest thing.  The
   definitions do NOT need to be orthogonal/disjoint.

   Consider the thing "Termination".  The Termination:

   *  Covers all aspects of "carrier" signal processing

   *  includes recursive definition of encapsulated forwarding

   *  includes all possible properties of termination for any signal
      (including those not yet defined)

   *  includes capabilities to extract signal content and further adapt
      to anther signal

   *  etc.

3.16.  Observation: Two distinct perspectives and viewpoints

   Considering a system taking a provider role, there are two distinct
   perspectives

   The external perspective (the effect) - "exposed"

   *  Capability (advertised to enable negotiation and selection)

   *  Intention (the agreement resulting from the selection at the end
      of negotiation)

   *  Achievement of intention

   The internal perspective (the realization)



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   *  Realizations (alternative system design approaches to achieve
      exposed capabilities)

   *  Specific chosen realization (the system to be deployed)

   *  Actual realization achievement

   Both perspectives are expressed using the same model pattern and
   model elements, i.e., the component-system pattern, where a component
   is described in terms of a system of components and components are
   specialized as appropriate (as discussed earlier).

   There are two viewpoints:

   *  that of the client where only the external perspective is
      available

   *  that of the provider where both the internal (which is private)
      and external perspective are available

   The provider also has control of the mapping between internal and
   external perspective.

   Note that:

   *  the provider may have distinct roles where each has access to a
      subset of the provider viewpoint.

   *  the perspectives and viewpoints apply to both the capabilities
      being controlled by the system and the capabilities supporting the
      control system (which are controlled by another system).

   *  the external perspective relates to "Customer Facing Service" (TM
      Forum, what is exposed to the customer) and the internal
      perspective to "Resource Facing Service" (how it is realized
      (roughly))

   *  At any arbitrary demarcation, the same approach may be applied

   *  The actual chosen demarcation may shift as the solution is
      developed and evolves

   *  This can be stated as how it looks from the outside and how it
      looks on the inside







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   This is discussed further in [ONF TR-512.8] where it is noted that a
   client talks through a provider port to the provider functions about
   the controlled system where that controlled system is presented as a
   projection that has been mapped to an appropriate abstraction of the
   underlying detail.

3.17.  Observation: Capability in more detail

   A Capability statement is the statement of visible effect of a thing
   and is not a statement of the specific realization of that thing.
   The visible effect may be complex.  The thing may have many ports and
   activity at one port may affect activity at another.  Capability
   statements will include performance and cost (environmental footprint
   etc.).

   It is important to recognized that the statement of capability is NOT
   exposing intellectual property related to how the capability is
   achieved.

   Expression of externally visible capability and expression of
   realization of that capability can both use a model of the same types
   of things, but the specific arrangement will often be very different
   as the externally visible capability is a severe abstraction of the
   internal realization where a subset of the capabilities of the
   underlying system are offered potentially in different terminology
   and in a different name space.

   The approach of expression of capability can be applied recursively
   at all levels of control abstraction from deep within the device to
   the most abstract business level.

3.18.  Observation: Occurrence

   As system is constructed from components.  Often a system will make
   repeated use of the same type of component.  Whilst in a realization
   of that system the components are considered as instances, in the
   design, they are clearly not instances.  But there are many.  The
   term "Occurrence" has been used in ONF work (see [ONF TR-512]).

   In a component-system approach, an Occurrence is a single use of a
   particular component type in a system design structure.  There may be
   many uses of that type in that system design structure, and hence
   many Occurrences, where each use of that type may have subtly
   different narrowing of capabilities to each other use and certainly
   different interconnectivity.

   Capability, intent and realization are all specified in terms of
   system structures and hence all require the use of Occurrence.



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   Considering the "progressive narrowing" observation earlier in this
   document, what is a singular thing at one level may result in several
   separate things at the next level, each of which is a slightly
   different narrowing of the definition of the original singular thing.
   These things are Occurrences.

   Hence, the progressive narrowing starts with a single Occurrence of
   thing at the first level and splits this into multiple Occurrence at
   the next and then each may split at the next etc.

   Note that:

   *  the pictures of devices in a network structure example diagram are
      essentially Occurrences.

   *  the presentation of an instance in a management view can be argued
      to also be an Occurrence.

   *  that through each progressive narrowing of definition, what was a
      single "type" at one level of narrowing may cause many
      "occurrences" at the next level.

   *  a type is simply an Occurrence with a particular definition where
      that Occurrence is used in the next level of definition as a type.

3.19.  Observation: One model

   From a model perspective there appears to be no relevant distinction
   between what can be requested and what can be achieved.  A single
   model representation of the things and their effect, based upon the
   recursive/fractal component-system pattern appears appropriate.

   The intention/expectation is expressed in terms of a structure of
   occurrence and what is realized is in terms of a similar structure of
   occurrence (where at the extreme the structure is exactly the same).

   There are however several stages and consequent perspectives:

   *  the original request (the expectation retained by the client)

   *  the accepted request (the intention, retained by the provider,
      normally the same as the expectation)

   *  the achievable outcome (expressed by the provider, normally the
      same as the intention)

   *  the current realization (more precise than the intention)




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   *  the effects of the realization in the perspective of the original
      request (achievement)

   *  the difference between the client expectation and the achievement
      (discrepancy)

   For example:

   *  the client may wish to request an E-Tree with particular
      characteristics including endpoints, bandwidth, temporal
      characteristics etc.

   *  the provider may accept this minus one endpoint.

   *  the provider may not be able to achieve the accepted request
      initially as some hardware is not yet in place

   *  the realization will provide subordinate details.

   *  the effect of the realization can be abstracted back, freed from
      some irrelevant detail, to form the achievement (reflecting the
      details of the original E-Tree request)

   *  the provider can represent the differences between the original
      request and the achievement

   For all of the above, the key model elements are a multi-pointed
   connection and a set of terminations.  The detail of the realization
   is supported by a recursion of multi-pointed connections.  There is
   no reason for different representational forms of the different
   stages of development.

3.20.  Observation: Partially satisfied request

   The original request from the client may not be satisfiable

   *  during the progression of activities formulating the solution and
      acting on that formulation

   *  initially, although it may be later

   *  at some intermediate stage in the lifecycle, although it was
      initially and will be again shortly

   *  ever






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   Where there is knowledge of a temporary shortfall, expression of what
   is achievable as a lifecycle of related statements appears necessary
   and beneficial.  Parts of this lifecycle appear to be definable
   within individual properties using the mechanism in the metamodel
   suggested by the various observation here.

3.21.  Observation: Other solution elements that benefit

   The progressive narrowing approach that yields levels of Occurrences
   where those Occurrences are defined in terms of semi-constrained
   properties (as discussed in this document) appears beneficial in the
   construction of:

   -Policy (as per general definition): The condition statement could
   benefit from a generalized metamodel approach to range etc.

   *  Profile/Template (for all the various interpretations of these
      terms): Various methods that support the specification of
      constraints in a single statement to be applied multiple instances
      simultaneously.

   The constraint statement would benefit modeling in general.  For
   example, in UML, OCL is an add-on that tends to be "beyond" the
   normal model.  An advancement to the essential metamodel would
   inherently include interaction constraints etc.

3.22.  Observation: Outcome and Experience

   The term Outcome is being used here to relate to the apparent/
   emergent structure/capability made available by the provider and the
   ongoing behavior of that structure/capability.

   The term Experience is being used here to relate to the client
   perception of the effect that the provider Outcome has (i.e., the
   client perception of the Outcome).  It can also be argued that the
   Experience is the client Outcome and that the provider Experience
   includes the feedback by the client on their overall experience of
   the provided capability etc.

   An Outcome/Experience may be a:

   *  Momentary event of set of events

   *  Constant state or set of states over time (first order)

   *  Constant change of state or set of state changes over time (second
      order)




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   *  ... (nth order)

   *  Change of state defined some algorithm or set of changes of state
      defined by a set of algorithms

   *  Etc.

   Both outcome and experience can be expressed in using the same
   approach discussed in this document.

   In the connectivity example discussed earlier, considering the
   client:

   *  the expectation for the Outcome is an E-Tree (a resource!)

   *  the Experience is effect of the E-Tree which is complex apparent
      adjacency (the true "service", a change of apparent proximity).

3.23.  Observation: Metamodel v Model

   The metamodel is a model that constrains one or more other model(s).
   The term metamodel is essentially about the role of the model in the
   relationship to other models.  The model with the metamodel role when
   related to another model influences that other model and is
   specifically designed to do so.

   A model taking a metamodel role may express how another related model
   may express properties to be represented.

   Clearly a model that takes a metamodel role is just a model and hence
   may have a related model that takes a metamodel role for it etc.

   Note that meta means "providing information about members of its own
   category" (Merriam Webster).

4.  Solution: Formulation

   The following subsections consider the observations from the earlier
   sections and point to aspects of a potential solution.

   The first few subsections consider the solution in general
   independent of specific realization.  The final subsection considers
   the applicability of YANG.  Some considerations in the realization
   independent sections are already supported by YANG, others are not.







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4.1.  Solution: Methodology

   Each type/structure/property is specified in terms of constraints
   narrowing prior definition/specification.  Note that this is a common
   approach, but the recursive nature is not well represented, and each
   level of the recursion tends to seem special.

   Examples are as discussed earlier:

   *  A standard may narrow an integer range

   *  A usage may narrow the standard integer range

   *  Etc.

   The prior definitions must be explicitly (efficiently) referenced.
   Note that this is a common approach but the specific usage here is
   distinct from normal usage.  Examples relate to earlier discussion:

   *  A prior definition may be used for several Occurrences in the same
      specification

   *  A definition syntax may be transformed, but the semantics cannot
      be changed, only narrowed

   *  A property may have preferred values etc.

   *  Etc.

4.2.  Solution: Considering the property

   Extending the approach could lead to a more uniform specification of
   properties in a control system context.

   Any property, e.g., temperature, may have combinations of the
   following features:

   *  A detector: Allowing opportunity for approximate, unknown, range
      etc. and allowing notification of change with definable approach
      to hysteresis etc.

   *  An associated control: Which has intent, achievement etc. and,
      especially where it takes time to take the control action, may
      have some progress on the action etc.

   *  Thresholds based alerts: Which has intent (as above) and which has
      an associated state (allowing opportunity for approximate etc.),
      notification etc.



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   *  Have inter-property interrelationships for any of the above

   *  Have Units for any of the above

   *  etc.

4.3.  Solution: Occurrence Specification

   Any property and its range of opportunities is stated in a
   specification.  Any invariant values in the specification need not be
   reported in the state of the "instance" (unless the instance is no
   longer behaving as defined in its specification).

   Ideally the metamodel should be such that, when a model designer
   chooses to define a property, they pick which of the above features
   are relevant and need not specify each separately.  This would lead
   to automatic name generation etc. where the name structure can be
   predefined.

   A uniform way of expressing each of the above features could be
   developed as could tooling to generate the representation (e.g.,
   YANG) for each feature given a property name.  The application of
   each feature to a property is essentially the occurrence of the
   feature.

4.4.  Observation: Uniformity of expression

   Using a uniform and consistent expression for "occurrences" at all
   levels of refinement naturally allows for expression of a mix of
   constraints and absolute values.

4.5.  Solution: Tooling support

   Clearly, tooling support will be vital for any initiatives in this
   area to be successful.

5.  Target and next steps

   There does not seem to be readily available terminology to label/
   define the concepts in the problem space

   *  Hence it has been difficult to discuss what properties the
      language needs to possess.

   *  Action: Improve terminology definitions

   It appears that there is not a good language suited to solve this
   problem fully.



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   *  This may only appear to be the case, i.e., there may be a language
      out there (as it has proved very difficult to describe the
      problem)

   *  Action: Continue to explore and refine

   It is possible that YANG could evolve to be more suitable

   *  YANG does not have all the necessary structures or recursion

   *  Progress sketch for a JSON form of YANG as an illustration of the
      unification of class and instance statement representation.  Work
      the proposal to suitable maturity (requirements first)

6.  Conclusion

   Tackling the challenge of modelling of boundaries leads to a more
   complete method of specification of gradual refinement of definition
   and of statement of "occurrences" including classes, instances and
   various forms between.

   This method allows for:

   *  Expression of range, preference and focus as a fundamental part of
      the metamodel

   *  Gradual refinement and recursive tightening of constraints as a
      native approach of the modeling technique

   Gradual refinement is required in many areas of the problem/solution
   space and this more complete method naturally allows for the
   necessary representation of uncertainty and vagueness.  The rigid
   boundary representation of the current approaches (e.g., class,
   instance) is accommodated within the method as a narrow case of
   application of the method.

   This softer and more continuous approach to specification refinement
   with the opportunity for uncertainty, ranges and biases better
   describes any real-world situation and hence appears more appropriate
   for an intelligent control solution (using AI/ML etc.) where that
   solution could take advantage of partial compatibilities etc.

   It appears that the enhancements to the language metamodel could be
   within, as extensions to, and compatible with current definitions of
   YANG as it appears that YANG is appropriately formed to accommodate
   such extensions.

   Note that the problem appears in expression:



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   *  Intent

   *  Capability

   *  Partial Visibility

   *  Planning

   *  Negotiation

   *  Policy

   *  Profile/Template

   *  Occurrence

   *  Etc.

7.  Security Considerations

   None

8.  IANA Considerations

   This document has no IANA actions.

9.  Informative References

   [ONF TR-512] TR-512 Core Information Model (CoreModel) v1.5 at
   https://opennetworking.org/wp- content/uploads/2021/11/TR-
   512_v1.5_OnfCoreIm-info.zip (also published by ITU-T as G.7711 at
   https://www.itu.int/rec/T-REC-G.7711/
   recommendation.asp?lang=en&parent=T-REC-G.7711-202202-I)

   [ONF TR-512.A.2] TR-512.A.2 Appendix: Model Structure, Patterns and
   Architecture (in Model Description Document within [ONF TR-512])

   [ONF TR-512.8]TR-512.8 Control (in Model Description Document within
   [ONF TR-512])

10.  Normative References

   [RFC2119]  Bradner, S., "Key words for use in RFCs to Indicate
              Requirement Levels", BCP 14, RFC 2119,
              DOI 10.17487/RFC2119, March 1997,
              <https://www.rfc-editor.org/info/rfc2119>.





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   [RFC8174]  Leiba, B., "Ambiguity of Uppercase vs Lowercase in RFC
              2119 Key Words", BCP 14, RFC 8174, DOI 10.17487/RFC8174,
              May 2017, <https://www.rfc-editor.org/info/rfc8174>.

Appendix A.  Appendix A - Problem/Solution Examples

   This appendix lists examples (to be expanded).

   *  A circuit pack with a fixed mapping that supports a narrow subset
      of the capability defined in the relevant standards...

   *  A slot in a shelf that takes specific circuit packs

   *  A temperature sensor with particular range and precision

   *  A detector that is temporarily absent

   *  A detector that is degraded due to some temperature issue

   *  A use of an ethernet termination in a particular configuration of
      functionality such as the ethernet termination in a G.8032 ring
      that deals specifically with the termination of signaling traffic

   *  A request for an e-line where the bandwidth requirement varies
      over the day

   *  A request for an e-line where there is an acceptable range of
      bandwidths and/or a cost profile for bandwidth

   *  A request for an e-tree where the connectivity requirement varies
      over the week

   *  An initial position for planning some infrastructure where the
      capacity of termination is known and the building is known, but
      not the specific device

   *  slicing where the request is for some range of capability and the
      solution is an approximation to that capability where the
      approximation is stated as a bounded space.

Appendix B.  Appendix B - Sketch of an enhanced YANG form

   In this appendix a sketch of a language, that is a development of
   YANG, that resolves some of the issues is set out.  The language is
   not completely formed, and it is not the intention that this
   necessarily be the eventual expression, this is simply used for
   illustrative purposes.




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B.1.  Progression

   Using this language, a progression of increasingly specific models
   can be set out (as set out in the main body of this document).  The
   refinements at each stage would be in terms of reduction of semantic
   scope compared to the previous stage.  At an early stage of
   refinement, the component-system pattern emerges.

   The language provides definitions for terminology (in a name space)
   where each term is defined by the specific narrowing (note that the
   terms are simply a human convenience).

   The progression is not a partition.  It does not divide the space up
   into a taxonomy.  The progression does lead to sets of capability
   where those sets may intersect etc.

   A traditional model is replaced by what is emergent at a stage in the
   recursion.  A label (in a label space) chosen for a semantic volume
   should not be reused for anything else.  Once defined the label
   should never be deleted, although it can be obsoleted (i.e., not
   expected to be used).

   If the label is encountered, its definition should be available such
   that it can be fully interpreted.  The label may apply in a narrow
   application and hence the narrowing definition should be available.

B.2.  Language

   As noted, it appears that there is not a good language suited to
   solve this problem fully.  This may only appear to be the case, i.e.,
   there may be a language out there, as it has proved very difficult to
   describe the problem (there does not seem to be readily available
   terminology for the concepts in the problem space) and hence it has
   been difficult to discuss what properties the language needs to
   possess.

   To cut through this, the best approach appeared to be to sketch a
   language and show how it could be applied to hopefully tease out an
   existing language that could then solve the problem (or so it can be
   a basis of a new language).

   As noted earlier, considering the general and apparently broad extent
   of the problem, it seems strange that there is not an appropriate
   machine interpretable language of expression available.  It is
   possible that existing languages can be used to deal with the problem
   in a somewhat cumbersome way and that this has not yet been observed.
   Cumbersomeness can be refined out over time.  Preferably there will
   not need to be Yet Another Language!



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B.3.  Key concepts

   Recursive narrowing appears to give rise to "occurrences", where each
   of a set of occurrences is in part the same as and in part different
   from each other.  Curiously:

   *  there also appears to be a parallel with the specific approach to
      specialization taken in ONF (and in YANG models using augment)
      where a "class" is actually a narrowed "occurrence" of a more
      general metaclass (see earlier discussion).  The distinction in
      the general thinking is that there are no specific meta-levels.
      Narrowing can take place through a recursive continuum until all
      properties have been constrained to absolute precision (which is
      actually never possible as there is always some uncertainty,
      rounding etc.).

   *  When all properties have been constrained the result is the
      statement of a unique instance at a moment in time (where each
      occurrence has a lifecycle which intertwines with the lifecycles
      of other occurrences).  But this instance is itself an opaque
      representation of the effect of underlying detail.

   *  this approach seems to point to some usages of the term "instance"
      being flawed and that actually the supposed instance is an
      "occurrence".

   Definitions may be of some type and may cover a subrange of that
   type.  Even in an occurrence that is traditionally called an
   instance, the property values may be ranges.  The key difference for
   the properties of an instance is that they are unlikely to be further
   decomposed.

B.4.  Observation

   At all levels of the recursion there is a mix of schema definition
   and absolute value (instance values).  So, some of the information in
   a spec looks like instance data and some like schema.  This should
   not be surprising when observing through the lens of recursive
   narrowing and of occurrence.

   Curiously a YANG model definition has instance like data and schema
   data in it.  For example, there is instance like data at the
   beginning of the definition with things like module, namespace,
   prefix etc.  YANG does not appear uniform in its representation of
   instance like data and schema data.

   The example language developed here attempts to achieve greater
   uniformity.



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B.5.  Progressing to the language

   Taking JSON as a language of expression of instances and setting out
   a YANG definition in a JSONized form appeared to allow a uniform
   blend of instance and schema.

   It has been recognized that YIN is a more well-structured form of
   YANG that points further towards this, and a JSONized form of YIN
   looked like the hand crafted JSONized YANG that has been constructed
   here (exploring the expression of recursive narrowing).

   JSON has also been simplified here in that every property value is
   considered as a string and hence in quotes (even numeric quantities).
   It is not intended that any eventual language is restricted in this
   way, the approach just simplifies the representation and resultant
   discussion.

   Note that regardless of the form of language chosen, there will be a
   need to enhance tooling etc.  It is intended that the approach should
   evolve in small backward compatible increments and hence it may be
   possible to identify value-justified increments in tooling.

B.6.  JSONized YANG

   The following two snippets show the instance-like header and the
   schema data in a JSONized form.

B.6.1.  JSONised Header

   The opening of a YANG module (called a header in this document) is
   normally of a form illustrated in the example below:

   module equipment-spec-xyz {

     yang version "1.1";

     namespace "urn:onf:otim:yang:spec-occurrence:equp-spec-xyz{uuid}";

     prefix equip;

   etc.

   In the JSONized form all of the fields are assumed to be "instance"
   values (where it is assumed that a higher level of specification has
   specified these).  The JSONized form of the example (extended with
   some other suggested fields) is:

   "module" : {



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  "name": "equipment-spec-xyz{uuid}"

  "yang-version" : "x.y",

  "namespace" : "urn:onf:otim:yang:spec-occurrence:equp-spec-xyz{uuid}",

  "prefix" : "equip",

  "import" : [

        {

              "name" : "module",

              "prefix" : "mod"

        }

        {

              ....


  "occurrence-encoding" : "JSON",  //Field to explain encoding

  "rule-encoding" : "OCL", //Field to explain encoding

  "utilized-schema": [ //Ref schema at next higher "occurrence" level

        {

              "namespace" : "urn:company:yang:holder-schema-xyz{uuid}",

              "prefix" : "holder"

        }

        {

              "namespace" : "urn:company:yang:tapi-spec",

              "prefix" : "tapi-spec"

        }

        {

              "namespace" : "urn:onf:otcc:yang:tapi-equipment",



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              "prefix" : "tapi-equipment"

              ...

        }

        {

              "namespace" : "urn:onf:otcc:yang:tapi-occurrence",

        ...

        }

        {

              "namespace" : "urn:company:yang:equp-schema-abc{uuid}",

              "prefix" : "equipment"

        }

        ...

  "augment":  [

        {

              "path" : "..."

        }

        ...

B.6.2.  JSONized body

   The core of a YANG module (called a body in this document) is
   normally of a form illustrated in the example of a fragment below:













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   grouping connection {

       list connection-end-point {

           uses connection-end-point-ref;

           key 'topology-uuid node-uuid nep-uuid cep-uuid';

           config false;

           min-elements 2;

           description "none";

       }

       list lower-connection {

           uses connection-ref;

           key 'connection-uuid';

   ....

   In the JSONized form all of the fields are assumed to be "instance"
   values (where it is assumed that a higher level of specification has
   specified these).  The JSONized form of the example (extended with
   some other suggested fields) is:























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       "grouping":{

           "name" : "connection",

           "list": {

               "name" : "connection-end-point",

               "uses" : "connection-end-point-ref",

               "key" : "topology-uuid node-uuid nep-uuid cep-uuid",

               "config" : "false",

               "min-elements" : "2",

               "description" : "none"

           },

           "list": {

               "name" : "lower-connection",

               "uses" : "connection-ref",

               "key" : "connection-uuid",

               "config" : "false",

               "description" : "none"

           },

   Notice the uniformity/consistency between the representations of the
   header and the body.

B.7.  Schema for the schema

   With this a YANG model can define a YANG model (within reason... and
   probably similar to other self-defining languages - improvements
   could probably be made to make this more possible).

   Considering an extract from tapi-equipment formulated in JSONized
   YANG:






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    "grouping":{

          "name":"common-equipment-properties",

          "description":"Properties common to all aspects of equipment",

          "leaf": {

                "name" : "asset-instance-identifier",

                "type" : "string",

                "description" : "none"

          },

          "leaf": {

                "name" : "is-powered",

                "type" : "string",

                "description" : "none"

          },

                "leaf": {

                "name" : "equipment-type-name",

                "type" : "string",

                "description" : "none"

          },

          "leaf": {

                "name" : "manufacture-date",

                "type" : "string",

                "description" : "none"

          },

          "leaf": {




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                "name" : "serial-number",

                "type" : "string",

                "description" : "none"

          },

          "leaf": {

                "name" : "temperature",

                "type" : "decimal64",

                "description" : "none"

          },

   It is expected that the above model would have been derived from a
   broader model and that it would reference that model.

   In the following development of the model a reference would be
   provided back to the model above.

   This could be used as a general definition, then constrained for a
   particular application as follows:

    "grouping":{

          "name":"common-equipment-properties",

          "description":"Properties common to all aspects of equipment",

          "leaf": {

                "name" : "asset-instance-identifier",

                "type" : "string",

                "pattern" : "^[0-9a-zA-Z]+"$, // A narrowing constraint.

                "description" : "none"

          },

          "leaf": {

                "name" : "is-powered",



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                "type" : "string",

                "supported-constraint" : "NOT_SUPPORTED",//A narrowing.

                "description" : "none"

          },

          "leaf": {

                "name" : "equipment-type-name",

                "type" : "string",

                "description" : "none"

          },

          "leaf": {

                "name" : "manufacturer-date",

                "type" : "string",

                "description" : "none"

          },

          "leaf": {

                "name" : "serial-number",

                "type" : "string",

                "description" : "none"

          },

          "leaf": {

                "name" : "temperature",

                "type" : {

                      "name":"decimal64",

                      "fraction-digits":"1", // A narrowing constraint.




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                       "range" : "0.0..100.0",

                       "precision":"+0.2,-0.2"

                },

                "units" : "Celcius", // A narrowing constraint.

                "description" : "The temperature of the boiler."

          },

   Which could be summarized with a reference to the earlier schema and
   then as follows, where the absent fields are unchanged from the
   earlier schema and the fields mentioned simply show the change/
   addition:



































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     "grouping":{

           "name":"common-equipment-properties",

           "utilized-schema" : "tapi-equipment", //The reference

           "leaf": {

                 "name" : "asset-instance-identifier",

                 "pattern" : "[0-9a-zA-Z]"

           },

           "leaf": {

                 "name" : "is-powered",

                 "supported-constraint" : "NOT_SUPPORTED"

           },

           "leaf": {

                 "name" : "temperature",

                 "fraction-digits": "1",

                 "range" : "0.0... 100.0",

                 "units" : "Celcius"

           },

   And eventually instance values can be mixed with schema...

    "grouping":{

          "name":"common-equipment-properties",

          "description":"Properties common to all aspects of equipment",

          "utilized-schema" : "tapi-equipment",

          "asset-instance-identifier" : "JohnsAsset"

          "leaf": {




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                "name" : "equipment-type-name",

                "type" : "string",

                "description" : "none"

          },

          "leaf": {

                "name" : "manufacturer-date",

                "type" : "string",

                "description" : "none"

          },

          "leaf": {

                "name" : "serial-number",

                "type" : "string",

                "description" : "none"

          },

          "leaf": {

                "name" : "temperature",

                "type" : "decimal64",

                "range" : "0.0... 100.0",

                "units" : "Celcius",

                "description" : "none"

          },










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   Notice that as with normal JSON the name of the property "asset-
   instance-identifier" is followed by its value (or json-object).  The
   "utilized-schema" has defined "asset-instance-identifier" and the
   utilization method hence allows the property to either be defined
   further or narrowed to a fixed value.  There are clearly "key words"
   such as "leaf" that will have been defined in an "earlier" schema, so
   something like:

     "field": {

           "name":"leaf",

           "type": "strings"

     ...

   And further there would need to be a definition of "name" and "type"
   etc. and their usage in a structure.

B.8.  An example of spec occurrence and rules

   This example detail will be added in a later version.

B.8.1.  Rough notes

   Considering an occurrence of holder in a spec for an equipment, there
   is a need to identify all compatible equipment types (i.e., that that
   holder can accommodate).  Each type would be associated with a
   general spec of capability and that spec would relate to the specific
   application (in the holder) either directly (as the holder is fully
   capable or the spec is specific to the holder) or via some variables
   in the spec (that allow modulation of the spec statements).

   There are also combinatorial rules.  For example, a slot may not be
   equipped if blocked by a wide card.  This can be represented
   by....Wide card

   It is possible that there are multi-slot compatibility rules.

   The functional capability may be simply the capability of the
   equipment type, but there is often functionality that emerges from a
   combination of hardware.

   In this case an equipment may support some fully formed capabilities
   and some capability fragments that need to be brought together with
   other fragments to support a meaningful function.





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   In some cases, functionality from one piece of hardware might compete
   with functionality from another or functionality might be completely
   nullified by the presence of another specific piece of hardware.

   The equipment-type-identifier is the reference to the equipment spec.
   This brings details of size and capability.

   It is assumed that the holder specification would provide width,
   position etc. and that there could be a general understanding of
   size, or there could be a more abstract representation to enable
   overlap to be accounted for.

B.9.  The current schema

   This detail will be added in a later version of this document.

B.10.  YANG tree

   This detail will be added in a later version of this document.

B.11.  Instance example

   This example detail will be added in a later version of this
   document.

B.12.  The extended schema

   This detail will be added in a later version of this document.

B.13.  Versioning considerations

   This detail will be added in a later version of this document.

Appendix C.  Appendix C - My ref / your ref

   This appendix will cover "my ref/your ref" naming in relationship to
   intention/expectation.  The detail will be added in a later version
   of this document.

Appendix D.  Appendix D - Occurrence

   An "occurrence" at one level of specification is a narrow
   ("specialized") use of an "occurrence" at the previous higher level
   of specification.  There will be many "occurrences" at a lower level
   derived from an "occurrence" at a higher level.  The "occurrences" at
   the lower level will be distinct from each other.





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   Considering the problem space, "Thing" has the broadest spread of
   semantics covering everything.  Function could be considered as a
   narrowed thing covering only functional aspects and not physical
   aspects.  Termination covers only those functions related to
   terminating a signal (and not those related to conveying it
   unchanged.

   Considering the formulation of a traditional model, a specific
   object-class (e.g., Termination Point) is a specific name for an
   "occurrence" at one level of narrowing ("specialization").  The name
   object-class is a specific "name" for an "occurrence" at the previous
   higher level.  That previous higher level is called the metamodel in
   this naming scheme.  This is more a narrowing of how to express as
   opposed to what to express.

   Considering the traditional model, "Thing" is effectively an object-
   class.  Considering "Component-System", "Thing" has ports/facets, as
   do all of its derivatives (unless, of course, they have been narrowed
   away).  The "Component-System" formulation is essentially a narrowing
   of the expression opportunity in the broadest of problem space
   considerations at a higher level than "Thing".  It effectively
   provides a quantized representation of a continuous space allowing
   representation of a refinement of conceptual parts.

   In the generalized "occurrence" approach, no specific names are given
   to the levels and the levels are intentionally not normalized.  The
   approach allows any number of levels, and the number of levels in one
   "branch" does not need to match the number of levels in another.  The
   approach allows for whatever degrees of gradual refinement are
   necessary.

   So, a traditional "instance" is also an "occurrence" where it is an
   "occurrence" of specific object- class, i.e., of an "occurrence" at
   the previous higher level.  The "instances" is a leaf in the
   metamodel structure.

   In the generalized "occurrence" approach there is no specific end
   leaf.  Even when the model level has only fully resolved specific
   values, it is possible to merge in a model with non-specific value
   "occurrences" and continue to refine.

   A specific occurrence:

   *  Is narrowing of a previously defined occurrence (where there may
      be many separate distinct narrowings defined at that "level", many
      occurrences

   *  Is a mixture of absolute values and definitions



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   *  May be a merge of narrowed previously defined occurrences (where
      the semantic phase is shifting)

   *  Is the basis for further narrowing

   It also appears that an absolute value of a property at one level may
   be considered as an unstated approximation of a non-fully resolved
   property at the next level down.  For example, a statement of 2 at
   one level, refines to 2+/- 15ppm over a short period at the next as
   the visibility "improves".  This seems to say that all levels have a
   natural uncertainty that may not be known and hence need not be
   stated.

Appendix E.  Appendix E - Narrowing, splitting and merging

E.1.  Narrowing

   On the most abstract level is "thing" - without any stated parameter,
   hence without any constraints.  "thing" is anything without
   restriction and can take any shape etc.  All possible properties are
   allowed without restriction (they do have to be declared, but there
   is no boundary as to what is allowed to be declared).  The declared
   properties are of "thing".  It is a semantic set including every
   possible behavior etc. and all parameters possible.

   At the next level of narrowing, some behaviors and hence possible
   parameters are eliminated and some constrained versions of allowed
   parameters are exposed.  At this point, a convenient name for the
   specific narrowing can be provided and later references.  However,
   this can also be considered still as "thing".

   In the most complete realization, the semantic boundary would be
   fully defined such that properties on the boundary were appropriately
   constrained and properties beyond the boundary eliminated.  For
   example, a termination-point cannot have a temperature.  So, an
   expression eliminating this possibility would be necessary and so on
   for all other properties that cannot be supported.  In a more
   practical implementation, most properties that are beyond the
   boundary can be assumed to be known to be beyond the boundary and
   only those with complex constraints need to be stated.

   When narrowing "thing", what it can be is reduced and hence so are
   the parameters that can be exposed.  For example, if it is not
   physical, I cannot expose the parameters for weight.

   As the "thing" is narrowed the properties that are allowed to be
   exposed reduces, but there is a tendency to have more properties
   exposed as more and more properties become constrained.  For example,



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   color may be irrelevant and hence not exposed or constrained for some
   of the broader "occurrences", but as the narrowing process approaches
   the useful definitions, the color becomes constrained and useful, and
   hence exposed.

   Through the narrowing process the set of opportunities becomes
   smaller and "lighter weight" (possibilities), but more is exposed
   (semantic mass reduces, semantic visibility increases).

   Consider an equipment.  It is a physical thing.  It may be narrowed
   to the point where it is constrained such that it can only be plugged
   into a slot.  It is still an equipment, albeit a constrained forms of
   the general equipment properties for an application.  The equipment
   has a property "requires-slot" set to true.  During the first
   formulation, color may be of no relevance and hence is not exposed.
   Just because it is not important does not mean that the equipment
   does not have a color, it means that it is not relevant.  It can take
   any color and I don't care.

   Later, the color becomes important and hence it is exposed and later
   still it becomes necessary to choose to constrain the allowable
   colors for an application.  It is still an equipment, but it has a
   spec that constrains what is allowed.  The spec is for a narrow form
   of equipment.  It can still be considered as an equipment even though
   it is a narrow case.  It can also be considered as a "thing" with
   exactly the stated property with some further directly stated
   constraints.

   Narrowing could be considered as pruning (removal of unwanted parts).
   For example, take a property (leaf/structure in general) from the
   higher occurrence and potentially:

   *  Reduce its legal range (perhaps to a single value) of the type.
      Note that changing the type is allowed if the new type covers the
      same semantics as the old type.  So, Integer to real seems OK and
      Enum to its corresponding semantic space dimensions seems OK
      (e.g., color Enum to RGB ranges)

   *  Specify the units where relevant (or change the units)

   *  Relate its value to other property values such that its value is
      constrained

   *  Remove the property completely

   *  Change its name (label) to one that represents the narrow version
      of the broader property, for example, component --> termination-
      point



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   This is how modelling is often carried out although it is never
   formally described as a method.  Consider the termination point, the
   model is for any connection at any layer etc, and there are
   "profiles" of parameters for particular technologies which augment
   the termination point.  The profiles may may add (actually expose)
   further parameters for the same technology or for new technologies,
   but termination point can never have weight as a parameter and
   certainly cannot be sat on!!

   YANG augment is the same process in general, so YANG is positioned
   appropriately to be the language for this approach.

   Interestingly, an AI solution may eventually prefer to use semantics
   closer to thing than to EthernetTerminationPoint as it can deal with
   the shades of specification of general things.

E.2.  Splitting

   Splitting semantics is relatively straight forward.  Two distinct
   occurrences each narrowed from the same higher-level occurrence where
   the two new occurrences have distinct characteristics.

E.3.  Merging

   As everything is an "occurrence" of thing, everything has a common
   highest level of thing.  When merging, it may be necessary to go some
   way back towards that common highest level.

   Where the two occurrences are disjoint in distinct characteristics
   and identical in common characteristics, merging is simply a union.
   The result may adopt the label of the shared higher level or may have
   a new label depending upon the labeling (naming) strategy.

   Where common characteristics are not identical:

   *  one may be a simple superset of the other in which case the
      superset is adopted.

   *  There may be contradictions in the two specifications in which
      case there needs to be a simple precedence, e.g., Not overrides
      Must,

   Where merging two (or more) properties from higher models into one
   property

   *  There must be a new name for this rephasing of the semantic if
      neither of the source properties were derived from an origin with
      the same breadth of space as the new property



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   *  One of the names can be taken if it earlier in the narrowing
      corresponded to the superset of the new merged result

   For example, TerminationPoint narrowed to have no OAM capabilities
   and then OAM picked up and merged in (again) at some later stage so
   that this is still TerminationPoint (but it is NOT OAM).

   For example, a narrow form of TerminationPoint (processes of traffic
   at a point) and a narrow form Connection (conveys traffic of space
   with no transformation) merged into a (strange) long termination that
   does some distributed processing of traffic.  This is neither a
   TerminationPoint nor a Connection.  It could revert to Component with
   full spec, or it could become a ProcessingSpan (or similar).

Appendix F.  Appendix F - A traffic example

   This example detail will be added in a later version of this
   document.

Acknowledgments

Contributors

   Martin Skorupski
   highstreet technologies
   Email: martin.skorupski@highstreet-technologies.com


Author's Address

   Nigel Davis
   Ciena
   Email: ndavis@ciena.com


















Davis                     Expires 27 April 2023                [Page 51]