| Table of Contents |
|---|
Existing Optimization Models
LIST OF OPTIMiZATION GOALS
- minimize
- maximize
LIST OF OBJECTIVE FUNCTIONS
- attribute
- sum
Minimize an unweighted value
...
| Code Block | ||||
|---|---|---|---|---|
| ||||
{
"minimize": {
"sum": [
{
"product": [
100,
{
"distance_between": [
"customer_loc",
"vG"
]
}
]
},
{
"product": [
200,
{
"hpa_score": [
"vG"
]
}
]
}
]
}
}
|
New Optimization Model
Objective Function Object
| Attribute | Required | Content | Values | Description |
|---|---|---|---|---|
| goal | Y | String | minimize, maximize | The goal of the optimization |
| objectiveoperation_function | Y | Objective Operation function Object | The objective operation function that has to be optimized |
Objective Operation function object
| Attribute | Required | Content | Values | Description |
|---|---|---|---|---|
| operationoperator | NY | String | sum, min, max | The operation which will be a part of the objective function |
| operands | NY | 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 |
operation-function operand object
| Attribute | Required | Content | Values | Description | |||
|---|---|---|---|---|---|---|---|
| weightnormalization | N | decimal | default: 1.0 | Weight of the operand | normalization object | Set of values used to normalize the operand | |
| weight | N | Decimal | Default: 1.0 | Weight of the function | |||
| operationobjective_function | N | Objective operation function object |
function operand object
| Attribute | Required | Content | Values | Description |
|---|---|---|---|---|
| normalization | N | normalization object | Set of values used to normalize the operand | |
| weight | N | Decimal | Default: 1.0 | Weight of the function |
| function | N | String | distance_between, latency_between, attribute | Function to be performed on the parameters |
| fucntion_params | N | dict | parameters on which the function will be applied. The parameters will change for each function. |
Examples
Scenario:
Scenario:
objective function - distance_between(demand, location) + distance_between(demand, location)
Normalization object
| Attribute | Required | Content | Values | Description |
|---|---|---|---|---|
| start | Y | Decimal | Start of the range | |
| end | Y | Decimal | End of the range |
JSON Schema
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|---|---|---|---|---|
|
Examples
1. Minimize an attribute of the demand
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{
"goal": "minimize",
"operation_function": {
| ||||
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{ "goal": "minimize", "objective_function": { "operation": "sum", "operands": [ { " "function": "distance_betweenattribute", "weight": 1.0, "params": { "demandattribute": "vGlatency", "locationdemand": "customerurllc_loccore" } } }, {], "functionoperator": "distance_betweensum", } } |
2. Minimize the sum of the distance between the demand and the customer location.
objective function - distance_between(demand, location) + distance_between(demand, location)
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|---|---|---|---|---|
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{ "weightgoal": 1.0"minimize", "operation_function": { "paramsoperator": {"sum", "operands": [ "demand": "vFW", { "locationfunction": "customerdistance_locbetween", "weight": 1.0, } "params": { } ] } } |
Scenario:
objective function - latency(demand) + latency(demand)
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|---|---|---|---|---|
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{ "goal"demand": "minimizevG", "objective_function": { "operation": "sum", "operandslocation": [ "customer_loc" { } }, { "function": "attributedistance_between", "weight": 1.0, "params": { "demand": "urllc_corevFW", "attributelocation": "latencycustomer_loc" } }, } {] } } |
Scenario:
Minimize the sum of latencies of slice subnets
objective function - latency(demand) + latency(demand)
| Code Block | ||||
|---|---|---|---|---|
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{ "functiongoal": "attributeminimize", "operation_function": { "weightoperator": 1"sum", "operands": [ { "function": "attribute", "weight": 1.0, "params": { "demand": "urllc_rancore", "attribute": "latency" } }, ] { } } "function": "attribute", "weight": 1.0, "params": { "demand": "urllc_ran", "attribute": "latency" } } ] } } |
Scenario:
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)) ) ]
| Code Block | ||||
|---|---|---|---|---|
| ||||
{
"goal": "maximize",
"objectiveoperation_function": {
"operationoperator": "sum",
"operands": [
{
"objectiveoperation_function": {
"operationoperator": "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"
}
}
]
},
"normalization": {
"start": 100,
"end": 1000
},
"weight": 2.0
},
{
"objectiveoperation_function": {
"operationoperator": "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"
}
}
} ]
},
"normalization": {
"start": 50,
"end": ]5
},
"weight": 1.0
}
]
}
} |
_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)
...
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)
Eg:
latency range: 50 ms to 5 ms
| candidate latency | Normalized value |
|---|---|
| 20 ms | 0.667 |
| 40 ms | 0.222 |
throughput range: 100 Mbps to 1000Mbps
| candidate throughput | Normalized value |
|---|---|
| 300 Mbps | 0.222 |
| 800 Mbps | 0.778 |