LIST OF OPTIMiZATION GOALS
- minimize
- maximize
LIST OF OBJECTIVE FUNCTIONS
- attribute
- sum
Minimize an unweighted value
Minimize a weighted value
Maximize an unweighted value
| Attribute | Required | Content | Values | Description |
|---|---|---|---|---|
| goal | Y | String | minimize, maximize | The goal of the optimization |
| objective_function | Y | Objective function Object | The objective function that has to be optimized |
Objective function object
| Attribute | Required | Content | Values | Description |
|---|---|---|---|---|
| operation | N | String | sum, min, max | The operation which will be a part of the objective function |
| operands | N | List of operand object | The operand on which the operation is to be performed. The operand can be an attribute or result of a function |
operand object
| Attribute | Required | Content | Values | Description |
|---|---|---|---|---|
| weight | N | decimal | default: 1.0 | Weight of the operand |
| objective_function | N | Objective function object | ||
| 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:
objective function - distance_between(demand, location) + distance_between(demand, location)
objective function - latency(demand) + latency(demand)
_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)
normalized_unit = func(lat, weight, unit)