Modelling Boundaries
draft-davis-netmod-modelling-boundaries-03
| Document | Type | Active Internet-Draft (individual) | |
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| Author | Nigel Davis | ||
| Last updated | 2024-03-16 | ||
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draft-davis-netmod-modelling-boundaries-03
WG Working Group N. Davis
Internet-Draft Ciena
Intended status: Informational 16 March 2024
Expires: 17 September 2024
Modelling Boundaries
draft-davis-netmod-modelling-boundaries-03
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 on a particular thing from a particular
perspective. 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 a 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 specify 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 . . . . . . . . . . . . . . . . . 6
3. Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . 6
3.1. Specific challenge areas - some terminology . . . . . . . 6
3.1.1. Specification of "Expectation" and "Intention" . . . 6
3.1.2. Specification of Capability . . . . . . . . . . . . . 7
3.1.3. Expression of Partial Visibility . . . . . . . . . . 7
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3.2. Observation: Progressive Narrowing of definition . . . . 8
3.3. Observation: Definition expansion . . . . . . . . . . . . 9
3.4. Observation: Expression of capabilities . . . . . . . . . 9
3.5. Observation: Application of expression of capability . . 10
3.6. Observation: Compatibility . . . . . . . . . . . . . . . 10
3.7. Observation: Defining the boundary . . . . . . . . . . . 12
3.8. Exploration: The nature of the solution . . . . . . . . . 13
3.9. Clarification: Complex blurry fuzzy boundaries . . . . . 13
3.10. Observation: Artificial Intelligence and uncertainty . . 15
3.11. Observation: Optimization under uncertainty . . . . . . . 15
3.12. Observation: Expectation-intention for all
interactions . . . . . . . . . . . . . . . . . . . . . . 16
3.13. Observation: Intention-Expectation interaction . . . . . 18
3.14. Observation: Intention-Expectation layering . . . . . . . 18
3.15. Observation: Instance state . . . . . . . . . . . . . . . 19
3.16. Observation: Event driven solutions . . . . . . . . . . . 20
3.17. Observation: Foldaway complexity . . . . . . . . . . . . 21
3.18. Exploration: Focusses boundaries & partial
descriptions . . . . . . . . . . . . . . . . . . . . . . 23
3.19. Observation: Two distinct perspectives and viewpoints . . 24
3.20. Observation: Capability in more detail . . . . . . . . . 26
3.21. Observation: Occurrence . . . . . . . . . . . . . . . . . 26
3.22. Observation: One model . . . . . . . . . . . . . . . . . 27
3.23. Observation: Partially satisfied request . . . . . . . . 29
3.24. Observation: Other solution elements that benefit . . . . 29
3.25. Observation: Outcome and Experience . . . . . . . . . . . 29
3.26. Observation: Metamodel v Model . . . . . . . . . . . . . 30
4. Solution: Formulation . . . . . . . . . . . . . . . . . . . . 31
4.1. Solution: Methodology . . . . . . . . . . . . . . . . . . 31
4.2. Solution: Considering the property . . . . . . . . . . . 32
4.3. Solution: Occurrence Specification formation . . . . . . 32
4.4. Observation: Uniformity of expression . . . . . . . . . . 33
4.5. Solution: Tooling support . . . . . . . . . . . . . . . . 33
4.6. Observation: Growing need . . . . . . . . . . . . . . . . 34
5. Target and next steps . . . . . . . . . . . . . . . . . . . . 34
6. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . 35
7. Security Considerations . . . . . . . . . . . . . . . . . . . 36
8. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 36
9. Informative References . . . . . . . . . . . . . . . . . . . 36
10. Normative References . . . . . . . . . . . . . . . . . . . . 36
Appendix A. Appendix A - Problem/Solution Examples . . . . . . . 36
A.1. Temperature sensor . . . . . . . . . . . . . . . . . . . 37
A.2. Temperature sensor features . . . . . . . . . . . . . . . 37
A.3. Temperature sensor application . . . . . . . . . . . . . 38
A.4. A circuit pack . . . . . . . . . . . . . . . . . . . . . 39
A.5. A slot in a shelf . . . . . . . . . . . . . . . . . . . . 40
A.6. Temporary loss of visibility . . . . . . . . . . . . . . 40
A.7. Degraded detection . . . . . . . . . . . . . . . . . . . 41
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A.8. Use in a configuration . . . . . . . . . . . . . . . . . 41
A.9. Bandwidth time variation . . . . . . . . . . . . . . . . 41
A.10. Intent . . . . . . . . . . . . . . . . . . . . . . . . . 42
A.11. Recursive narrowing/refinement during negotiation . . . . 42
A.12. Capability slice . . . . . . . . . . . . . . . . . . . . 42
Appendix B. Appendix B - Sketch of an enhanced YANG form . . . . 43
B.1. Progression . . . . . . . . . . . . . . . . . . . . . . . 43
B.2. Language . . . . . . . . . . . . . . . . . . . . . . . . 43
B.3. Key concepts . . . . . . . . . . . . . . . . . . . . . . 44
B.4. Observation . . . . . . . . . . . . . . . . . . . . . . . 44
B.5. Progressing to the language . . . . . . . . . . . . . . . 45
B.6. JSONized YANG . . . . . . . . . . . . . . . . . . . . . . 45
B.6.1. JSONised Header . . . . . . . . . . . . . . . . . . . 45
B.6.2. JSONized body . . . . . . . . . . . . . . . . . . . . 47
B.7. Schema for the schema . . . . . . . . . . . . . . . . . . 49
B.8. An example of spec occurrence and rules . . . . . . . . . 56
B.8.1. Rough notes . . . . . . . . . . . . . . . . . . . . . 56
B.9. The current schema . . . . . . . . . . . . . . . . . . . 57
B.10. YANG tree . . . . . . . . . . . . . . . . . . . . . . . . 57
B.11. Instance example . . . . . . . . . . . . . . . . . . . . 57
B.12. The extended schema . . . . . . . . . . . . . . . . . . . 57
B.13. Versioning considerations . . . . . . . . . . . . . . . . 57
Appendix C. Appendix C - My ref / your ref . . . . . . . . . . . 57
Appendix D. Appendix D - Occurrence . . . . . . . . . . . . . . 57
Appendix E. Appendix E - Narrowing, splitting and merging . . . 59
E.1. Narrowing . . . . . . . . . . . . . . . . . . . . . . . . 59
E.2. Splitting . . . . . . . . . . . . . . . . . . . . . . . . 61
E.3. Merging . . . . . . . . . . . . . . . . . . . . . . . . . 61
Appendix F. Appendix F - A traffic example . . . . . . . . . . . 62
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . 62
Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . 62
Author's Address . . . . . . . . . . . . . . . . . . . . . . . . 62
1. Introduction
The essential challenge being considered in this draft 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 definition of that thing.
The constrained definition of a thing requires the expression of a
boundary that surrounds all allowed/possible values for
characteristics of that thing.
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The draft 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 of 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.
Considering the apparent prevalence of need for expression of
progressive refinement of ranges and uncertainty, it seems strange
that there should be no readily available language, so part of the
purpose of this draft 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 draft 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 sketch will seed advancements in the YANG language in
this area.
1.1. Observation: Terminology
We all recognize the challenge with 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 our collective usage of a term spreads across a very
wide space where each of us only aligns with a subspace of that
usage.
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.
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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.
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 statements
of preference and of acceptable value ranges etc.
The specification 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 and
hence may be experienced (observed etc.) by the client.
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
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* service
3.1.2. Specification of Capability
This is a statement of opportunity for behavior 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, where the expression
covers all detailed aspects of the 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:
* Advertising of solutions (both at a commercial boundary and for
components inside a system where the advertisement is of
abstracted capability)
* Negotiation towards contract (where capability requirement and
offer are refined)
* Planning infrastructure buildout (where capability of solutions
and of components is required)
* Intent solution formation (intent is the result of negotiation,
expressing boundaries on the required solution capability)
* Any situation where specialized components need to be assembled
(where minimally the capability for assembly will be expressed)
3.1.3. Expression of Partial Visibility
Any real environment will suffer imprecision, loss and disruption.
Any statement made about properties (behavior, 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)).
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This leads to the need, for expression of any property, to include
the opportunity 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
using inheritance), which provides precise definitions of properties
etc. (current YANG models are essentially 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.
* 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
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* 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 naturally 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
progression of narrowing. For example, the vendor solution may
extend with proprietary features not defined in the standard, but
instead derived from some related process.
Further, there will be evolution and growth so the next development
of the standard etc. may extend/adjust the statements.
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 express the capability of
the component and indeed some of the progression. The depth of
expression of capability will depend upon the application, however,
it is expected that it will be necessary to have a comprehensive
statement expressing restrictions and constraints covering
combinatorial effects within the solution.
The client is required to interpret capabilities expressed. To best
facilitate this, the capabilities should be expressed in normalized
uniform machine interpretable form. The capability statements should
be available to the client at any stage of its operation. The
capability statements could be published by the provider directly or
indirectly via some other publication service.
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As the capabilities of each instance of a function may differ and
vary over time in a complex way, expressing restrictions/difference
using traditional classification technique appears to be inadequate;
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 functions (of both the control
provider and control client)
Each of the above:
* is always an abstraction/view of the underling real system
* needs to cover 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).
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]
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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 this is not overly relevant)
The result of the intersection is usually a narrower statement of
capability than the statement for the two components (at 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
If any of the mandatory application interaction semantic elements are
eliminated by the intersection process, 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.
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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 as the solution space evolves.
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 and/or limited interest in
positioning (don't know, somewhere round about here, don't care,
that's precise enough)
* 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.)
* have associated probability (likelihood of a particular position)
and preference (for a particular position)
The above considerations apply similarly to intent specification,
capability specification and partial visibility.
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, as note above, or may be dependent
upon some other variable property.
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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
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
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.
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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.
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.
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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.
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 clarity of
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: Optimization under uncertainty
As networks advance in scale and complexity, interest in the
optimization of their design and deployment naturally follows. While
"classic" forms of optimization work with point values for the
parameters that define the optimization objectives and constraints,
there continues to be important parallel development of methods that
work with quantifiable forms of uncertainty in the problem
parameters. The approach of robust optimization for example
typically seeks the best solution that is still feasible even when
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problem parameters achieve their worst-case values within a given
range of uncertainty. A probabilistic relative of these techniques
(in some contexts referred to as stochastic programming), can be
applied when the problem parameters follow a given probability
distribution over their range.
An important example parameter type that plays a central role in
telecom network optimization is the matrix of source-destination
traffic demands (i.e., "the traffic matrix").
In real-world settings, each value in this matrix carries with it
both measurement uncertainty as well as its intrinsic statistical
variance. On intra-day time scales modal variations (e.g. day-night
peaks and troughs) can be observed overlaid with (typically short)
episodes of "anomalous" traffic. In certain longer time scale
contexts, the intraday variations are less of a concern while longer
term growth trends (and uncertainty around how to extrapolate from
current trends) are of primary concern.
The above situation is a strong example of the value of working with
ranged values, in this case representing the associated intrinsic
variance and/or estimation errors of the traffic matrix parameters.
Doing so allows sophisticated forms of robust and stochastic
optimization to be applied that would not be possible if only point
average estimates were retained and available for optimization and
other purposes.
Apart from traffic matrix, models of endogenous risk (e.g. equipment
defect) or exogenous risk (e.g. regional flood/fire/power outage) if
quantified statistically can factor together into optimizations in a
way that allows management of worst-case scenarios while pursuing
primary optimization objectives. This ties in as well with
observation that advanced AI/ML applied to suitably dense datasets
provides probability distributions of the problem parameters,
expediting application of robust or stochastic form of optimization
as outlined above.
Summarizing, from the above there appears fairly clear value from an
optimization perspective of network models that facilitate and invite
the expression of ranged parameters.
3.12. Observation: Expectation-intention for all interactions
The idea of Expectation/Intention as discussed earlier can be further
developed to cover all interactions including instance configuration.
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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.
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 the operation SET of 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).
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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 nothing more than a 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 (see later for further explanation
of 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 (as they are not of interest and are
essentially noise).
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.
3.13. 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.
3.14. Observation: Intention-Expectation layering
As a result of a negotiation between two interacting systems, the
provider commits to intend to supply some capability to the client
(which the client expects). As noted earlier, negotiation may
degenerate into imposition. To supply this capability, the provider
needs to use the services of underlying systems and hence it is the
client in interactions with these other systems (client and provider
are roles with respect to a specific interaction, provider is not an
all-encompassing role of a system etc.). Where a provider is adding
value, it will combine capabilities of its providers in such a way as
to provide to its clients the necessary capability. This combination
is complex and outside the scope of this document. At the lower
parts of this hierarchy will be real physical providers (at which
point the intention-expectation relationships degenerate into the
relationships of physics).
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Note that here a physical thing is something that can be "measured
with a ruler".
3.15. 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. In this example, errors are detected
and counted over a second. If there are more than a particular
number of errors in a second, the second is declared as severely
errored. The number of severely errored seconds are counted over a
period (perhaps 15 minutes) and if more than a particular number of
severely errored seconds are counted in that period (e.g., 15
minutes), the severely errored second alert is raised.
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).
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3.16. Observation: Event driven solutions
In a control solution, there will be various dependent systems that
need to share information in a timely (real time) fashion so as to be
able to take optimum control action. As the information space of the
control solution is likely to be vast, but change is likely to be
relatively rare, it appears most appropriate to couple dependent
systems via a streaming interface such as gNMI STREAM or TAPI
Streaming (where the event stream essentially includes both current
state and change). The streaming solution focusses on sourcing
information on change from the place where the change occurs and this
approach achieves both optimum use of resources and most timely
awareness of change.
In general, it is unlikely for a system providing event streams to
(be able to) guarantee order of reporting of dependent items. As a
consequence, assembling and maintaining a view of the structure of
the information provided by another system via one or more streams is
somewhat like assembling a jigsaw (the pieces do not arrive in
order).
In addition the representation of semantics in the provider system is
likely to be (very) different from that in the client. The
representations will probably differ in semantic granularity and
semantic phase (boundary positioning between semantic units) such
that a unit of meaning in one system corresponds to fragments of
units of meaning in the other system.
Considering the above, as the streams, from one or more providers,
are consumed by the client, its view will emerge from the initial
unplaced fragments, skeletons of structure and shells of entities to
a nearly complete view of current state where that view is
essentially eventually consistent but, assuming that there is ongoing
change, is never complete.
In addition, as noted earlier, there may be issues with access to
some information which will then leave some entities incomplete for
significant periods of time.
Hence in general, through formation and maintenance of the view,
considering the semantic granularity/phase differences, any property
of an entity may be of uncertain value or only partially known.
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In some cases, there may be several alternative possible arrangements
of the information and a client system design may be such that it
needs to choose one arrangement as it forms the structure. It is
possible that that choice is subsequently understood by the client,
as a result of further information, to be incorrect so as to cause
the client to need to refactor the structure.
It may be necessary for the client to provide the emerging view it is
forming to its clients. It may be that the partial view is quite
suitable for the client's clients to take an action. Any data should
be provided as early as possible (along with the time of it becoming
true in an event timestamp). It is OK to send a TerminationPoint
with a reference to a TerminationPoint that is not yet known or a
TerminationPoint with some but not all properties present. The
representation of this emerging view requires expression of uncertain
boundaries.
In any solution it may be necessary to deal with conflicting data
where two sources report on the same resource for the same timeframe
but the reports are not aligned. In these cases it may also be
necessary for a system to report the conflicting data to its clients.
For this case, the representation needs to be designed to support
expression of multiple values for a single simple property where each
value may also carry an indication of the probability of its
correctness.
3.17. Observation: Foldaway complexity
It was noted in an earlier section that "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.".
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:
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"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"
}
}
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:
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"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 but that only allows the single
value temperature.
Ideally, considering the common requirements across all properties,
the terms used in the schema nested within the property name (where
an example of a term is "acceptable-range") would be standardized
etc.
3.18. Exploration: Focusses boundaries & 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 exposes behavior. A functional
thing is not physical, although it must be realized eventually by
physical things and hence physical things have associated functional
things. Functional things have ports, as this is where the behavior
is exposed (although the ports need not be represented under some
circumstances).
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 discovered/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.
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The progression above is essentially, specialization by narrowing of
focus. The broadest "Thing" has all possible characteristics and
capabilities (including many unknown characteristics and
capabilities). Specific semantics relate to the model of a specific
thing where that is derived from the narrowing of the broadest thing.
The definitions of things 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 another signal
* etc.
3.19. 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 (causing the client to experience the
desired outcomes)
The internal perspective (the realization)
* Realizations (alternative system design approaches to achieve
exposed capabilities)
* Specific chosen realization (the system to be deployed)
* Actual realization achievement
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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 system may have internal components with 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 terms defined by TM Forum to
"Customer Facing Service" (which is essentially what is exposed to
the customer) and the internal perspective to "Resource Facing
Service" (which is essentially how it is realized (roughly))
* At any arbitrary demarcation, the same approach may be applied
from the broadest inter-business demarcations right down to
demarcations deep within a device
* The actual chosen demarcation may shift as the solution is
developed and as it evolves
* This can be stated as how it looks from the outside (as an opaque
box - not "black box" in the strictest of senses as internal
behavior can be sensed from the outside) and how it looks on the
inside
This is discussed further in [ONF TR-512.8] where it is noted that a
client talks through a provider port to the provider control
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.
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3.20. 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 (as the externally visible capability is
emergent from the intricate assembly of the capabilities of the
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.
3.21. Observation: Occurrence
A system is constructed from components. Often a system will make
repeated use of the same type of component where each usage will be
distinct from each other. 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]) as a term an item of the
many.
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 of narrowing 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.
3.22. Observation: One model
From a model perspective there appears to be no relevant distinction
between expression of what can be requested and expression of how
that 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 how that is realized is in terms of a similar
structure of occurrence (where at the extreme the structures are
exactly the same as the exposed capability was expressed at the
finest possible granularity exposing everything).
There are however several stages and consequent perspectives:
* the original request (the initial expectation retained by the
client and progressed through negotiation to a final agreement)
* the accepted request (the intention, retained by the provider,
after agreement (normally the same as the expectation) retained by
the client after the agreement)
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* the achievable outcome (expressed by the provider, normally the
same as the intention)
* the current realization as exposed to the client (more precise
than the intention as the constraints of the intention are not
absolute single values and hence the current settings/states are
usually more precise)
* the actual realization as understood by the provider and not
exposed to the client (more detailed and significantly different
in structure to that exposed to the client and sufficient to fully
describe the solution that realizes the agreed outcomes)
* 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 at the different
stages of development.
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3.23. 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
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.
3.24. 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.
3.25. Observation: Outcome and Experience
The term Outcome is being used here to relate to the apparent/
emergent structure/capability made available by the provider to the
client and the ongoing behavior of that structure/capability.
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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
client Experience is the client's 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 or set of events (and the client's perception of
the effect of the event(s))
* Constant state or set of states over time (first order... and the
client's perception of the effect of the ongoing constant
state(s))
* Constant change of state or set of state changes over time (second
order... and the client's perception of the constantly changing
state(s))
* ... (nth order)
* Change of state defined some algorithm or set of changes of state
defined by a set of algorithms (complex landscape... and the
client's perception of traversing this landscape_
* Etc.
Both outcome and experience can be expressed in using the same
approach discussed in this document (although the model of experience
will be a significant abstraction, ultimately emotional).
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 and
the feeling of closeness and immediacy).
3.26. Observation: Metamodel v Model
The concept of metamodel involves a model that constrains one or more
other model(s). The term metamodel is essentially about the role of
a 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.
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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) where, in this case, the consideration is
the category of models.
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.
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 (whereas here each level
is considered just another level in the progression).
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 (shifted etc.), they can only be narrowed
* A property may have preferred values etc.
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* 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 value, unknown
value, value 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.
* Threshold based alert: Which has intent (as above) and which has
an associated state (allowing opportunity for approximate etc.),
notification etc.
* Have inter-property interrelationships for any of the above
* Have Units for any of the above
* etc.
4.3. Solution: Occurrence Specification formation
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 features,
sketched in the previous section, 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.
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4.4. Observation: Uniformity of expression
A uniform expression for Occurrence could be applied at all levels of
the progression of narrowing/refinement from the statements of most
general capable to the statement of the most resolved form (the
traditional instance). This expression form must allow for a mix of
constraints and absolute values. Ideally, each statement of absolute
value will be as compact as it is in a traditional instance language
and each statement of constraint will be as clear and concise as
possible.
A uniform expression form at all levels will maximize tooling
usefulness and minimize the need to learn varieties of structure
patterns etc.
4.5. Solution: Tooling support
Clearly, tooling support will be vital for any initiatives in this
area to be successful. The following areas would benefit from
tooling:
* model pattern construction
* occurrence formation supporting derivation from less refined
occurrences, formation of rules etc.
* property expansion and formation of rules for expanded properties
* validation of occurrence conformance
* occurrence visualization
* generation of code supporting occurrence
* etc.
When constructing a model it would be highly beneficial if patterns
for occurrences of YANG structures were constructed and made
available such that a seed property could drive tooling to construct
derivative properties (see Observation: Instance State above). For
example the seed property "temperature" could drive tooling using
patterns for threshold property structures etc. to generat YANG for:
* current state
* upper threshold
* lower threshold
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* watermark
* etc.
4.6. Observation: Growing need
Several activities are underway in IETF that begin to shine a light
on the need for mechanisms and approaches highlighted in this draft.
For example:
* T-NBI activity in CCAMP is setting out examples of occurrences of
network structures to guide towards consistent realisations to
improve interoperability. A method for forming occurrences from
the model entities would be highly beneficial.
* Plug parameters activity in CCAMP is identifying properties
relevant to optical plug control and is encountering inconsistent
formation of derivative properties. Tooling support for
construction of properties from a seed would be highly beneficial
bringing improved consistency and reducing the probability of
missing properties.
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.
* 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)
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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 promotes:
* 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:
* Intent
* Capability
* Partial Visibility
* Planning
* Negotiation
* Policy
* Profile/Template
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* 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])
[ONF TR-512.7] TR-512.7 Specification (in Model Description Document
within [ONF TR-512])
[ONF TAPI] ONF Transport API SDK 2.4.0 at
https://github.com/OpenNetworkingFoundation/TAPI/releases/tag/v2.4.0
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/rfc/rfc2119>.
[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/rfc/rfc8174>.
Appendix A. Appendix A - Problem/Solution Examples
This appendix sets out some examples to illustrate usage of the
capabilities set out in the main body of this document.
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A.1. Temperature sensor
Temperature is a general property of a physical environment where
there are several different scales and temperature, like all
properties, may be influenced and observed. The property temperature
can be applied to both measurement and control, when considered for
measurement, the property is read only. This is the first of a
recursion of narrowings.
An ideal temperature sensor would operate over the entire range of
all possible temperatures but would be read only. Any particular
type of real temperature sensor operates within a sub-range of all
possible temperatures and with particular resolution, precision and
accuracy (that might vary with temperature). The property
temperature, when used as part of the specification of a real type of
temperature senor will need to be bounded and constrained so as to
define these ranges. Perhaps the range is from -50.535 C to
+100.0012 C (note the chosen units will also need to be identified)
with a resolution of .001 C for the lower temperatures worsening to a
resolution of .003 C with following a specific equation etc. As the
specification applies to a a set of real manufactured things, and
recognizing that the manufacturing process is imprecise, the values
will also have to be toleranced. So, the upper temperature may be
+100.0012 C +/- 0.001 C. This is further narrowing.
In a particular usage of the temperature sensor, the valid range may
be further narrowed so whilst the temperature sensor may have a
significant negative range, the usage may not take advantage of this
and it may be constrained to express temperatures from +10 C to +50
C, and the precision further constrained so that it only exposes a
single decimal place. A further narrowing.
This is a specific case of the general case of specification of a
detailed capability.
A.2. Temperature sensor features
It is likely that in some designs for use of the specific temperature
sensor additional features will be provided such as threshold
crossing alerts and upper/lower watermark etc. In this case ideally,
when building the specifications to describe the temperature sensor
and its associated features, the property temperature would have been
expanded using the "Occurrence Specification formation" method
described earlier where the designer would "pick which of the feature
patterns are relevant". The expectation is that the designer would
simply reference each pattern in the specification and "need not
specify each separately". The various feature patterns selected
during the specification design would be represented in the
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expression of the Occurrence in an abstract form and expanded at run
time.
The patterns would lead to Occurrences with explicit threshold
properties, but these would be of a normalize form from case to case.
The same threshold pattern could be used for a temperature measure
and a power measure where the pattern yields property names. For
example, "temperature-high-threshold" and "power-high-threshold".
This is a specific case of the method of definition using patterns as
opposed to explicit expansions.
A.3. Temperature sensor application
Considering the temperature sensor discussed above, it is possible
that in a design several sensors of the same type may be used. These
occurrences may all have the same roles in the design, or they may
have very distinct roles. For example, there may be four sensors of
the same type on a specific type of circuit pack. In the design, one
of the sensors may be placed at the bottom and one at the top of the
circuit pack, as the circuit pack is to be used in a force air cooled
rack. The bottom sensor is measuring in-flow temperature and the top
one out-flow. These two sensors may operate over the same range etc.
and both reference the same constraint specification, although they
are clearly distinct occurrences and have different position-role
names.
Each of the other two sensor occurrences may be used in another role
to measure the specific temperature of a particular sub-unit in the
circuit pack, e.g., a CPU, where in this case there are two CPU
occurrences. The application of the senor to a CPU brings a
different set of constraints. There may also be a need for an alert
when a specific temperature has been exceeded etc. These two sensor
occurrences have the same spec as each other but not as the first
pair discussed above. In this case ideally, the property temperature
would have been defined using the "Occurrence Specification
formation" method.
It is possible that not all of the features specified for the sensor
are used in the application or perhaps some features are used in a
constrained form. In this case, a further narrowing is performed,
and new, more refined occurrence specifications are constructed.
When a client interrogates the system for its capabilities, the
various occurrence specifications that provide details of the
features will be reported.
Thus is a specific case of the general case of narrowing of
capability.
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A.4. A circuit pack
Clearly, it is vital to not just know the components and their
features, but also the arrangement of those components. There may be
several dimensions to the arrangements including physical positioning
and functional positioning where the latter would need to describe
interconnectivity between occurrences and flow of signals etc.
between the occurrences.
In the case of the temperature sensors discussed above these were
considered positioned on a circuit pack and related to units of
functionality on the circuit pack. The sensors of air flow
temperature may simply require physical positioning data in the
occurrence specification. The CPU sensors will require a stronger
relationship to the specific CPU. Neither require any functional
modelling.
Consider a circuit pack with traffic functional capability. This
circuit pack will have occurrences of interface, termination-point,
potentially vrf etc. these will all support some subset of the
corresponding standards, may support some proprietary capabilities
and will be arrangeable in various configurations depending upon the
specific capabilities and restrictions of the circuit pack.
There may be several distinct occurrences of a specific type of
termination point and several occurrences of another specific type.
Each of the types can be defined as an occurrence and then each of
the specific occurrences of termination-point can reference one or
other of the type occurrences.
There may be two specific occurrences of termination-point that have
a fixed relationship by design. This can be set out as part of the
circuit pack type occurrence spec using a simple relationship rule
occurrence (e.g., a "must connect" rule). There may be semi-flexible
relationships between a collection of occurrences, and these can be
set out in the circuit pack type spec using relationship rule
occurrences. For example,
* any interface of occurrence type "trib" may connect to any
interfaces of occurrent type "line"
* any interface of occurrence type "line" may connect to any
interface of occurrence type "line"
But occurrence type "trib" may not connect to occurrence type "trib"
so that rule is not stated.
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The approach described for representation of connectivity
restrictions is partially supported by [ONF TAPI] and is described in
[ONF TR-512.7] in more detail.
There are many more examples such as a circuit pack with a fixed
mapping that supports a narrow subset of the capability defined in
the relevant standards.
This is a specific case of the general case of specification of a
capability.
A.5. A slot in a shelf
For device with a backplane (an equipment) that has slots that
support field replaceable circuit packs (equipments) and for a
circuit pack that have slots that support SFPs (equipments) it is
usually the case that several different types of equipment can be
plugged in any particular slot. To cater for this, the equipment,
e.g., the backplane, specification would identify slot occurrences
and for each would reference the specification for each compatible
equipment. In some cases when a particular equipment type is
inserted in a particular slot its capabilities are reduce, perhaps
due to thermal considerations or access to the backpane bus etc. In
these cases, an additional stage of narrowing would be applied to
create a new equipment specification for the particular slot
application.
It is often true that some functionality emerges from specific
combination of circuit pack. Here a combinatorial specification
would be created to explain the emergent behavior from the
combination.
This is a specific case of the general case of specification of
compatibility.
A.6. Temporary loss of visibility
In some applications the reporting of a particular detector may be
mandatory. It is possible that under some circumstances the detector
value cannot be read (e.g., due to a communication issue inside the
NE, because the unit that hosts the measurement is restarting etc.).
Under these circumstances it is necessary to report that the detector
value is not available. This should be within the normal property
definition and ideally the YANG metamodel would allow a string
statement "value not available" or similar in a field that is defined
as an Integer or as another more complex structure.
This is a specific case of the general case of loss of visibility.
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A.7. Degraded detection
Considering the detector further, it is possible that some
environmental factor temporarily or permanently degrades the quality
of a detector output. It is important that this degradation is
reportable as an aspect of the detector output. Ideally this
degradation would be conveyed as part of the detector value and that
the method for conveying information on the degradation would be part
of the metamodel for the language (as discussed in elsewhere in this
document).
In some cases, the value may be used in combination with other values
to make a single abstract statement, that are available. It is
possible
This is a specific case of the general case of loss of visibility.
A.8. Use in a configuration
Consider an application of some resources. It is generally the case
that the same type of resource will be used in various places in the
application. Consider use of an ethernet termination in a particular
configuration of functionality such as an G.8032 ring where the
ethernet termination (interface) deals specifically with the
termination of signaling. In this application the termination has a
specific subrange of acceptable vids and has a particular
relationship to other terminations in the solution. These
restrictions need to be conveyed in the model of the application and
ideally. Ideally thw ability to convey these restrictions would be
an inherent aspect of the metamodel for the language such that the
use of a termination, i.e., the occurrence could be declared with its
specific subrange of allowable values and its specific restricted
associations to other termination points.
This is an example of a point on a progressive narrowing of
definition and an example of Occurrence.
A.9. Bandwidth time variation
There could be a request for an e-line where the bandwidth
requirement varies over the day and where that variation is dependent
upon the setting of other properties. Specification here would
benefit from an inherent capability in the metamodel of the language
of expression of the property definition to cater for time variation
and interrelationship such that any temporal properties and
interproperty interrelationships can be specified as a natural part
of the language.
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Taking this further, assume that for this example: - the bandwidth is
specified by an integer in bits/second and that this is sufficient to
deal with the full range of variability (clearly this is a
simplification for the example). - the temporal characteristic is
specified by a normalized temporal expression that allows for a
variety of repeat and calendar-based strategies, but for this example
is simply 1000000 bits/second for even clock hours and 0 for odd
clock hours. - the bit rate depends upon the value of another
property, "load-factor" which is an integer with a range of 1-10, by
some defined algorithm, here simply the product of bandwidth and
load-factor
Ideally the specification of the bandwidth within the definition
"integer" would provide an opportunity to state (or reference) the
temporal characteristic and the relationship to load-factor such that
the statement of Integer could include complex detail as opposed to
just one value when complexity is required, but would fold-away to a
simple form when a simple single value is to be stated.
This is an example of complex fuzzy boundaries.
A.10. Intent
A request for an e-line where there is an acceptable range of
bandwidths and/or a cost profile for bandwidth or some cost/bandwidth
combination and where this bandwidth is perceived by the client.
A.11. Recursive narrowing/refinement during negotiation
An initial position for planning some infrastructure where the
capacity of termination is known and the building is known, but not
the specific device. Through negotiation the details are refine to
the point where sufficient is stated for the client. This may still
not be a fully refined termination point as the cabling to the chosen
device has not yet been resolved. The choice of termination can be
made by the provider as a result of the activity to satisfy the
intent.
A.12. Capability slice
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.
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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.
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).
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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!
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.
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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.
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;
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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" : {
"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"
}
{
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"namespace" : "urn:company:yang:tapi-spec",
"prefix" : "tapi-spec"
}
{
"namespace" : "urn:onf:otcc:yang:tapi-equipment",
"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
Wade Cherrington
Ciena
Email: wcherrin@ciena.com
Amal Karboubi
Ciena
Email: akarboub@ciena.com
Sonny Rasmussen
Ciena
Email: sorasmus@ciena.com
Author's Address
Nigel Davis
Ciena
Email: ndavis@ciena.com
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