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Table of Contents

Existing Optimization Models

Minimize an unweighted value

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Code Block
languagejs
collapsetrue
{
    "minimize": {
        "sum": [
            {
                "product": [
                    100,
                    {
                        "distance_between": [
                            "customer_loc",
                            "vG"
                        ]
                    }
                ]
            },
            {
                "product": [
                    200,
                    {
                        "hpa_score": [
                            "vG"
                        ]
                    }
                ]
            }
        ]
    }
}

New Optimization Model

Normalization???

unique solutions ???

Objective Function Object

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AttributeRequiredContentValuesDescription
operatorYString

sum, min, max

The operation which will be a part of the objective function
operandsY

List of operand object

EIther an operation-function or a function

The operand on which the operation is to be performed.

The operand can be an attribute or result of a function 

inverseNBooleandefault: FalseFlag to specify whether the objective function has to be inverted.

operation-function operand object

decimaldefault operand
AttributeRequiredContentValuesDescription
normalizationNnormalization object
Set of values used to normalize the operand
weightNDecimalDefault: 1.0Weight of the function
operation_functionNoperation function object

function operand object

NAttributeRequiredContentValuesDescription
normalizationNnormalization object
Set of values used to normalize the operand
weightNDecimalDefault: 1.0Weight of the function
functionNString

distance_between,

latency_between, attribute

Function to be performed on the parameters
fucntion_paramsNdict

parameters on which the function will be applied.

The parameters will change for each function.

Normalization object

Examples

1. Minimize an attribute of the demand

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languagejs
collapsetrue

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AttributeRequiredContentValuesDescription
startYDecimal
Start of the range
endYDecimal
End of the range

JSON Schema

View file
nameopt_schema.json
height250


Examples


1. Minimize an attribute of the demand

Code Block
languagejs
collapsetrue
{
    "goal": "minimize",
    "operation_function": {
        "operandoperands": [
            {
                "function": "attribute",
                "params": {
                    "attribute": "latency",
                    "demand": "urllc_core"
                }
            }
        ],
        "operator": "sum"
    }
}

...

Code Block
languagejs
collapsetrue
{
   "goal": "maximize",
   "operation_function": {
   "operator": "sum",
   "operands": [
      {
         "operation_function": {
             "operator": "min",
             "operandoperands": [
                 {
                      "weight": 1.0,
                      "function": "attribute",
                      "params": {
                         "demand": "urllc_core",
                         "attribute": "throughput"
                      }
                 },
                 {
                      "weight": 1.0,
                      "function": "attribute",
                      "params": {
                         "demand": "urllc_ran",
                         "attribute": "throughput"
                      }
                 },
                 {
                      "weight": 1.0,
                      "function": "attribute",
                      "params": {
                         "demand": "urllc_transport",
                         "attribute": "throughput"
                      }
                 }
             ]
         },
         "weightnormalization": 2.0{
       },     "start": 100,
  {          "operation_functionend": 1000
   {      },
         "inverseweight": true 2.0 
      },
      {
         "operation_function": {
             "operator": "sum",
             "operandoperands": [
                 {
                     "weight": 1.0,
                     "function": "attribute",
                     "params": {
                         "demand": "urllc_core",
                         "attribute": "latency"
                      }
                 },
                 {
                     "weight": 1.0,
                     "function": "attribute",
                     "params": {
                         "demand": "urllc_ran",
                         "attribute": "latency"
                      }
                 },
                 {
                     "weight": 1.0,
                     "function": "attribute",
                     "params": {
                         "demand": "urllc_transport",
                         "attribute": "latency"
                      }
                 }
             ]
         },
         "weightnormalization": 1.0 {
            "start": 50,
            "end": 5
 }     ]  } }

_bw = [100, 200, 300]

ran_nssi → property bw → func(slice_profile[])

core_nssi  → property bw → func(slice_profile[])

tn_nssi  → property bw→ func(slice_profile[])

Maximize (min (ran_nssi_bw, core_nssi_bw, tr_nssi_bw))

Max  [ sum ( W_bw *  min (ran_nssi_bw, core_nssi_bw, tr_nssi_bw), 1/(W_lat * ( sum (w1 * ran_nssi_lat, w2 core_lat, W3* tn_lat)) ) ]

Min/max operator:  list of operands

Sum operator: list of operands

prod operator: weight, operand

normalized_unit = func(bw, weight, unit)

...

,
         "weight": 1.0
      }
   ]
 }
}


normalization:

function(value, range(start, end), weight)

All ranges are converted to 0 to 1. The inverse operation is not needed , since it is already implied in the range.

normalized value = (value - start) / (end-start)

...

latency range: 50 ms to 5 ms

candidate latencyNormalized value
20 ms0.667
40 ms0.222

throughput range: 100 Mbps to 1000Mbps

candidate throughputNormalized value
300 Mbps0.222
800 Mbps0.778

Impact Analysis

API  - no impact

Controller

Template version upgrade

New parser for the optimization model

Data - no impact

Solver

A new solver for the model (recursive solver?)

...