diff --git a/src/orchestration_config.json b/src/orchestration_config.json
index 160dd2af5bf3b2f222cc8dc48b3f21ea2c02cd48..b93e40bbe9098aadb21fc8e8077e36657189ccd5 100644
--- a/src/orchestration_config.json
+++ b/src/orchestration_config.json
@@ -4,23 +4,27 @@
"MODEL_FILE": "ITSystem.mo",
"MODEL_NAME": "ITSystem",
"SIMULATION_TIME": 100,
- "START_TIME": 8,
- "END_TIME": 13,
- "TIME_UNIT": "hour",
- "OPTIMIZATION_PARAMETERS": {
- "activeCores": {
- "bounds": [1, 4],
- "type": "int"
- },
- "cpuFrequency": {
- "bounds": [1.0, 3.0],
- "type": "float"
- }
+ "TIME_CONFIG": {
+ "START_TIME": 8,
+ "END_TIME": 13,
+ "TIME_UNIT": "hour"
},
- "EVALUATION_PARAMETERS": {
- "performance": "performance",
- "remaining_energy": "remainingEnergy",
- "energy_consumption": "energyConsumption"
+ "OBJECTIVES": [
+ {"name": "remainingEnergy", "maximize": true},
+ {"name": "performance", "maximize": true}
+ ],
+ "TUNABLE_PARAMETERS": {
+ "PARAMETERS": ["activeCores", "cpuFrequency"],
+ "PARAM_BOUNDS": {
+ "activeCores": {
+ "bounds": [1, 4],
+ "type": "int"
+ },
+ "cpuFrequency": {
+ "bounds": [1.0, 3.0],
+ "type": "float"
+ }
+ }
},
"INPUT_PARAMETERS": {
"available_energy": "availableEnergy",
@@ -28,5 +32,12 @@
},
"CRITERIA": {
"GOAL_EXPRESSION": "evaluation_results['performance'] >= simulation_inputs['user_demand']"
- }
+ },
+ "PLOT_CONFIG": {
+ "PLOT_X": "",
+ "PLOT_Y": "",
+ "PLOT_TITLE": "",
+ "ENABLE_PLOT": false
+ },
+ "N_JOBS": -1
}
\ No newline at end of file
diff --git a/src/orchestration_configurator.py b/src/orchestration_configurator.py
index 21949ee7e4b05fd0e68b12ba05a3ca6c222c356d..f496ab91163d069b7910205d9b2e1e06ebe464ca 100644
--- a/src/orchestration_configurator.py
+++ b/src/orchestration_configurator.py
@@ -18,17 +18,18 @@ def build_model(omc, model_name):
build_result = omc.sendExpression(f'buildModel({model_name})')
return build_result
-def simulate_and_evaluate(parameters, simulation_time, simulation_inputs, global_config):
+def simulate_and_evaluate(parameters, simulation_time, simulation_inputs, orchestration_config):
# General setup and configuration
- model_file = global_config['MODEL_FILE']
- model_name = global_config['MODEL_NAME']
- param_types = {param: details['type'] for param, details in global_config['OPTIMIZATION_PARAMETERS'].items()}
+ model_file = orchestration_config['MODEL_FILE']
+ model_name = orchestration_config['MODEL_NAME']
+ param_types = {param: details['type'] for param, details in orchestration_config['TUNABLE_PARAMETERS']['PARAM_BOUNDS'].items()}
+
# Create a temporary directory to avoid GUID mismatch issues
temp_dir = tempfile.mkdtemp()
- evaluation_parameters = global_config['EVALUATION_PARAMETERS']
- input_parameters = global_config['INPUT_PARAMETERS']
- goal_expression = global_config['CRITERIA']['GOAL_EXPRESSION']
+ evaluation_parameters = {obj['name']: obj['name'] for obj in orchestration_config['OBJECTIVES']}
+ input_parameters = orchestration_config['INPUT_PARAMETERS']
+ goal_expression = orchestration_config['CRITERIA']['GOAL_EXPRESSION']
try:
omc = init_omc_session(temp_dir, model_file)
@@ -80,17 +81,17 @@ def read_data_from_file(filename):
data.append((time_value, *map(int, values))) # Combine time value with other data
return data
-def adaptive_control_loop(data, moo_wrapper, global_config):
- start_time = global_config['START_TIME']
- end_time = global_config['END_TIME']
- simulation_time = global_config['SIMULATION_TIME']
- input_keys = list(global_config['INPUT_PARAMETERS'].keys()) # List of input parameter keys
+def adaptive_control_loop(data, moo_wrapper, orchestration_config):
+ start_time = orchestration_config['TIME_CONFIG']['START_TIME']
+ end_time = orchestration_config['TIME_CONFIG']['END_TIME']
+ simulation_time = orchestration_config['SIMULATION_TIME']
+ input_keys = list(orchestration_config['INPUT_PARAMETERS'].keys()) # List of input parameter keys
report = []
for entry in data:
time_value, *input_values = entry
if start_time <= time_value < end_time:
- print(f"Processing {global_config['TIME_UNIT']} {time_value}")
+ print(f"Processing {orchestration_config['TIME_CONFIG']['TIME_UNIT']} {time_value}")
# Create a dictionary of inputs
simulation_inputs = dict(zip(input_keys, input_values))
@@ -109,7 +110,7 @@ def adaptive_control_loop(data, moo_wrapper, global_config):
for best_parameters in parameter_list:
try:
evaluation_results, goal_satisfied, parameters, depletion_time = simulate_and_evaluate(
- best_parameters, simulation_time, simulation_inputs, global_config)
+ best_parameters, simulation_time, simulation_inputs, orchestration_config)
except Exception as e:
print(f"Simulation error: {e}")
continue
@@ -119,25 +120,11 @@ def adaptive_control_loop(data, moo_wrapper, global_config):
# Generate the report for each hour
if goal_satisfied:
- report.append(f"{global_config['TIME_UNIT'].capitalize()} {time_value}: Goal satisfid with configuration {parameters}. Simulation ran for {depletion_time} seconds out of {simulation_time} seconds.")
+ report.append(f"{orchestration_config['TIME_CONFIG']['TIME_UNIT'].capitalize()} {time_value}: Goal satisfid with configuration {parameters}. Simulation ran for {depletion_time} seconds out of {simulation_time} seconds.")
else:
- report.append(f"{global_config['TIME_UNIT'].capitalize()} {time_value}: No sufficient configuration found. Simulation ran for {depletion_time} seconds out of {simulation_time} seconds.")
+ report.append(f"{orchestration_config['TIME_CONFIG']['TIME_UNIT'].capitalize()} {time_value}: No sufficient configuration found. Simulation ran for {depletion_time} seconds out of {simulation_time} seconds.")
# Print the final report
print("\nFinal Report:")
for line in report:
- print(line)
-
-if __name__ == "__main__":
- # Load the orchestration configuration from orchestration_config.json
- with open(orchestration_config_path, 'r') as f:
- orchestration_config = json.load(f)
-
- # Read data from the specified data file
- data = read_data_from_file(orchestration_config['DATA_FILE_PATH'])
-
- # Initialize the MOO4ModelicaWrapper with the path to the MOO4Modelica config and the orchestration configuration
- moo_wrapper = MOO4ModelicaWrapper(config_path=orchestration_config['CONFIG_PATH'], global_config=orchestration_config)
-
- # Run the adaptive control loop with the loaded data and configuration
- adaptive_control_loop(data, moo_wrapper, orchestration_config)
\ No newline at end of file
+ print(line)
\ No newline at end of file
diff --git a/src/orchestration_wrapper.py b/src/orchestration_wrapper.py
index 07c97f1243a6812f9951d1c8f976668ab70d832b..095075c420b5d484233e2001c9547eaca29fc58b 100644
--- a/src/orchestration_wrapper.py
+++ b/src/orchestration_wrapper.py
@@ -5,25 +5,43 @@ import json
import os
from optimize_main import run_optimization
+import json
+import os
+from optimize_main import run_optimization
+
class MOO4ModelicaWrapper:
- def __init__(self, config_path, global_config):
+ def __init__(self, orchestration_config_path, config_path):
+ self.orchestration_config_path = orchestration_config_path
self.config_path = config_path
- self.global_config = global_config
- self.load_config()
- self.model_file = global_config['MODEL_FILE']
- self.model_name = global_config['MODEL_NAME']
+ self.load_configs()
+ self.update_config_file()
+
+ def load_configs(self):
+ with open(self.orchestration_config_path, 'r') as f:
+ self.orchestration_config = json.load(f)
- def load_config(self):
with open(self.config_path, 'r') as f:
self.config = json.load(f)
+ def update_config_file(self):
+ # Update config with orchestration config
+ self.config['MODEL_NAME'] = self.orchestration_config['MODEL_NAME']
+ self.config['MODEL_FILE'] = self.orchestration_config['MODEL_FILE']
+ self.config['SIMULATION_STOP_TIME'] = self.orchestration_config['SIMULATION_TIME']
+ self.config['PARAMETERS'] = self.orchestration_config['TUNABLE_PARAMETERS']['PARAMETERS']
+ self.config['PARAM_BOUNDS'] = self.orchestration_config['TUNABLE_PARAMETERS']['PARAM_BOUNDS']
+ self.config['OBJECTIVES'] = self.orchestration_config['OBJECTIVES']
+ self.config['PLOT_CONFIG'] = self.orchestration_config['PLOT_CONFIG']
+ self.config['N_JOBS'] = self.orchestration_config['N_JOBS']
+
+ with open(self.config_path, 'w') as f:
+ json.dump(self.config, f, indent=4)
+
def update_config(self, simulation_inputs, simulation_time):
- # Modify the configuration with new parameters
- self.config['PARAMETERS'] = list(self.global_config['OPTIMIZATION_PARAMETERS'].keys())
- self.config['PARAM_BOUNDS'] = self.global_config['OPTIMIZATION_PARAMETERS']
+ # Update only the simulation-specific parameters
self.config['SIMULATION_STOP_TIME'] = simulation_time
for input_param, value in simulation_inputs.items():
- self.config[self.global_config['INPUT_PARAMETERS'][input_param]] = value
+ self.config[self.orchestration_config['INPUT_PARAMETERS'][input_param]] = value
# Save the updated configuration to a file
with open(self.config_path, 'w') as f:
diff --git a/src/orchestrator.py b/src/orchestrator.py
index f229fce4bf900313a85c52f9e55fa405f2ddd038..7c067e482cd8a545e7c5fb9fecee65c5c0d90f98 100644
--- a/src/orchestrator.py
+++ b/src/orchestrator.py
@@ -3,7 +3,6 @@
import json
import os
-from optimize_main import run_optimization
from orchestration_wrapper import MOO4ModelicaWrapper
from orchestration_configurator import adaptive_control_loop, read_data_from_file
@@ -13,20 +12,20 @@ orchestration_config_path = os.path.join(base_path, 'orchestration_config.json')
def main():
# Load the orchestration configuration
with open(orchestration_config_path, 'r') as f:
- global_config = json.load(f)
+ orchestration_config = json.load(f)
# Get paths from the orchestration configuration
- data_file_path = os.path.join(base_path, global_config['DATA_FILE_PATH'])
- config_path = os.path.join(base_path, global_config['CONFIG_PATH'])
+ data_file_path = os.path.join(base_path, orchestration_config['DATA_FILE_PATH'])
+ config_path = os.path.join(base_path, orchestration_config['CONFIG_PATH'])
# Read data from the specified data file
data = read_data_from_file(data_file_path)
# Initialize the MOO4ModelicaWrapper with the path to the MOO4Modelica config and the orchestration configuration
- moo_wrapper = MOO4ModelicaWrapper(config_path=config_path, global_config=global_config)
+ moo_wrapper = MOO4ModelicaWrapper(orchestration_config_path=orchestration_config_path, config_path=config_path)
# Run the adaptive control loop with the loaded data and configuration
- adaptive_control_loop(data, moo_wrapper, global_config)
+ adaptive_control_loop(data, moo_wrapper, orchestration_config)
if __name__ == "__main__":
main()
\ No newline at end of file