def main():
# Parse arguments
args = parse_args()
if not args.seed:
args.seed = random.randint(1, 9999)
logging.basicConfig(level=logging.INFO)
logging.getLogger("coordsim").setLevel(logging.WARNING)
# Creating the results directory variable where the simulator result files will be written
network_stem = os.path.splitext(os.path.basename(args.network))[0]
service_function_stem = os.path.splitext(
os.path.basename(args.service_functions))[0]
simulator_config_stem = os.path.splitext(os.path.basename(args.config))[0]
results_dir = f"{PROJECT_ROOT}/results/{network_stem}/{service_function_stem}/{simulator_config_stem}" \
f"/{DATETIME}_seed{args.seed}"
# creating the simulator
simulator = Simulator(os.path.abspath(args.network),
os.path.abspath(args.service_functions),
os.path.abspath(args.config),
test_mode=True,
test_dir=results_dir)
init_state = simulator.init(args.seed)
log.info("Network Stats after init(): %s", init_state.network_stats)
nodes_list = [node['id'] for node in init_state.network.get('nodes')]
nodes_with_capacity = []
for node in simulator.network.nodes(data=True):
if node[1]['cap'] > 0:
nodes_with_capacity.append(node[0])
sf_list = list(init_state.service_functions.keys())
sfc_list = list(init_state.sfcs.keys())
ingress_nodes = get_ingress_nodes_and_cap(simulator.network)
# we place every sf on each node of the network with some capacity, so placement is calculated only once
placement = get_placement(nodes_with_capacity, sf_list)
# Uniformly distributing the schedule for all Nodes with some capacity
schedule = get_schedule(nodes_list, nodes_with_capacity, sf_list, sfc_list)
# Since the placement and the schedule are fixed , the action would also be the same throughout
action = SimulatorAction(placement, schedule)
# iterations define the number of time we wanna call apply()
log.info(f"Running for {args.iterations} iterations...")
for i in tqdm(range(args.iterations)):
_ = simulator.apply(action)
# We copy the input files(network, simulator config....) to the results directory
copy_input_files(results_dir, os.path.abspath(args.network),
os.path.abspath(args.service_functions),
os.path.abspath(args.config))
# Creating the input file in the results directory containing the num_ingress and the Algo used attributes
create_input_file(results_dir, len(ingress_nodes), "LB")
log.info(f"Saved results in {results_dir}")
def main():
# Simulator params
network = 'triangle.graphml'
args = {
'network': f'../../../../params/networks/{network}',
'service_functions': '../../../../params/services/abc.yaml',
'resource_functions': '../../../../params/services/resource_functions',
'config': '../../../../params/config/legacy_config.yaml',
'seed': 9999,
'output_path': f'test-out/{network}'
}
# Setup logging
timestamp = datetime.now().strftime('%Y-%m-%d_%H-%M-%S')
os.makedirs(f'{args["output_path"]}/logs', exist_ok=True)
logging.basicConfig(
filename=f'{args["output_path"]}/logs/'
f'{os.path.basename(args["network"])}_{timestamp}_{args["seed"]}.log',
level=logging.INFO)
logging.getLogger('coordsim').setLevel(logging.INFO)
simulator = Simulator(test_mode=True)
# Setup algorithm
algo = StaticTriangleAlgo(simulator)
algo.init(os.path.abspath(args['network']),
os.path.abspath(args['service_functions']),
os.path.abspath(args['config']),
args['seed'],
args['output_path'],
resource_functions_path=os.path.abspath(
args['resource_functions']))
# Execute orchestrated simulation
algo.run()
def create_simulator(agent_helper):
"""Create a simulator object"""
from siminterface.simulator import Simulator
return Simulator(agent_helper.network_path,
agent_helper.service_path,
agent_helper.sim_config_path,
test_mode=agent_helper.test_mode,
test_dir=agent_helper.config_dir)
def test_gym_registration(self):
config = get_config(AGENT_CONFIG)
simulator = Simulator(NETWORK, SERVICE, SIM_CONFIG)
env = GymEnv(agent_config=config,
simulator=simulator,
network_file=NETWORK,
service_file=SERVICE)
np.random.seed(123)
env.seed(123)
def test_min_max_delay(self):
config = get_config(AGENT_CONFIG)
simulator = Simulator(NETWORK, SERVICE, SIM_CONFIG)
env = gym.make('rlsp-env-v1',
agent_config=config,
simulator=simulator,
network_file=NETWORK,
service_file=SERVICE)
self.assertEqual(env.min_delay, 15)
self.assertEqual(env.max_delay, 45)
def test_step(self):
config = get_config(AGENT_CONFIG)
simulator = Simulator(NETWORK, SERVICE, SIM_CONFIG)
env = gym.make('rlsp-env-v1',
agent_config=config,
simulator=simulator,
network_file=NETWORK,
service_file=SERVICE)
np.random.seed(123)
env.seed(123)
env.reset()
action = env.action_space.sample()
env.step(action)
def test_step(self):
config = get_config(agent_config)
simulator = Simulator(network, service, sim_config)
env = gym.make('rlsp-env-v1',
agent_config=config,
simulator=simulator,
service_requirement_file=service_requirement,
network_file=network,
service_file=service)
np.random.seed(123)
env.seed(123)
obs = env.reset()
logger.info(f"obs {obs}")
# action = env.action_space.sample()
# action = [0.1528252, 0.19189513, 0.13835746, 0.5151016, 0.8268603, 0.11794249,
# 0.07534754, 0.8041661, 0.6766331, 0.83818173, 0.74750483, 0.2683317,
# 0.1885326, 0.17871094, 0.48484454, 0.80052173, 0.5470235, 0.939061,
# 0.7532571, 0.95109504, 0.7161905, 0.437634, 0.8504298, 0.56406283,
# 0.44520622, 0.9043397, 0.7369696 ,0.06333494, 0.85315746 ,0.35849094,
# 0.7802861, 0.42221898, 0.00383798 ,0.5678534 , 0.24563274 ,0.7632712 ,
# 0.8775916, 0.5324118 , 0.40174866 ,0.5244014 , 0.53869325 ,0.62608093,
# 0.55334944, 0.65927726 ,0.3466312 ,0.81105894, 0.5835827 ,0.4352289,
# 0.01409177, 0.68956935, 0.2725983 ,0.83922625, 0.12063584 ,0.85230696,
# 0.24010704, 0.7814054 , 0.6302035 ,0.7396873 ,0.3951772 ,0.42432162,
# 0.8822647 , 0.5477109 , 0.6531822 ,0.8758906 ,0.12640443, 0.31692567,
# 0.54074305, 0.7312232 , 0.40281135 ,0.46530938 ,0.29194754 ,0.1864658,
# 0.906782 , 0.73796546, 0.9524628 ,0.9118524 ,0.8770285 ,0.57136434,
# 0.6312382 , 0.5789188 , 0.14968178 ,0.41891995 ,0.09121216 ,0.01003964,
# 0.6886566 , 0.13875785, 0.99779034 ,0.36943817 ,0.5710171 ,0.41438,
# 0.81586087, 0.14191775, 0.2810072 ,0.8571065 ,0.83860654 ,0.2865804,
# 0.17616676, 0.11686828, 0.66831094 ,0.27806306 ,0.24364603 ,0.3952267,
# 0.1256759 , 0.5283989 , 0.7713088 ,0.01707859 ,0.86026347 ,0.96787435,
# 0.76898026, 0.24870834, 0.02020283 ,0.26120338 ,0.11047094 ,0.0451458,
# 0.7435941 , 0.14921127, 0.29213443 ,0.22803156 ,0.34240273 ,0.7448049,
# 0.34957966, 0.6426194 , 0.8075939 ,0.00796008 ,0.961782 ,0.8310099,
# 0.9726601 , 0.3459133 ]
action = [1, 0, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1]
logger.info(f"action is : {action}")
env.step(action)
def main():
args = parse_args()
if not args.seed:
args.seed = random.randint(1, 9999)
# os.makedirs("logs", exist_ok=True)
# logging.basicConfig(filename="logs/{}_{}_{}.log".format(os.path.basename(args.network),
# DATETIME, args.seed), level=logging.INFO)
# logging.getLogger("coordsim").setLevel(logging.WARNING)
# logging.getLogger("bjointsp").setLevel(logging.INFO)
# Creating the results directory variable where the simulator result files will be written
network_stem = os.path.splitext(os.path.basename(args.network))[0]
service_function_stem = os.path.splitext(
os.path.basename(args.service_functions))[0]
simulator_config_stem = os.path.splitext(os.path.basename(args.config))[0]
results_dir = f"{PROJECT_ROOT}/results/{network_stem}/{service_function_stem}/{simulator_config_stem}" \
f"/{DATETIME}_seed{args.seed}"
# creating the simulator
# initializing the simulator with absolute paths to the network, service_functions and the config. files.
simulator = Simulator(os.path.abspath(args.network),
os.path.abspath(args.service_functions),
os.path.abspath(args.config),
test_mode=True,
test_dir=results_dir)
init_state = simulator.init(args.seed)
# log.info("Network Stats after init(): %s", init_state.network_stats)
# assuming for now that there is only one SFC.
sfc_name = list(init_state.sfcs.keys())[0]
sf_list = list(init_state.sfcs.get(sfc_name))
sf_delays_dict = init_state.service_functions
nodes_list = [node['id'] for node in init_state.network.get('nodes')]
ingress_nodes, node_cap = get_ingress_nodes_and_cap(simulator.network)
# Getting the Mean Flow Data rate and flow size from the simulator_config.yaml file
with open(args.config, "r") as f:
conf = yaml.load(f, yaml.SafeLoader)
flow_dr_mean = conf.get('flow_dr_mean')
flow_size = conf.get('flow_size_shape')
run_duration = conf.get('run_duration')
inter_arrival_mean = conf.get('inter_arrival_mean')
flow_duration = (float(flow_size) / float(flow_dr_mean)
) * 1000 # Converted flow duration to ms
# Getting Processing delay from Service_functions file
with open(args.service_functions, "r") as f:
service_func = yaml.load(f, yaml.SafeLoader)
processing_delay = service_func['sf_list'][
sf_list[0]]['processing_delay_mean']
# The template object is fixed, so it is created just once and used throughout for the 'place' fx of BJointSP
template = create_template(sfc_name, sf_list, sf_delays_dict)
# Since after the init() call to Simulator we don't get any traffic info back
# we can't create the source needed for 'place' function of BJointSP,
# So we for just the first 'place' call to BJointSP create a source with just ingress nodes having *
# *vnf_source as the vnf in it and date_rate of flow_dr_mean from the config file
num_flows = run_duration / inter_arrival_mean
overlapping_flows = math.ceil(
(num_flows * (processing_delay + flow_duration)) / run_duration)
source_list = []
j = 1
for i in range(len(ingress_nodes)):
flows = []
for _ in range(int(overlapping_flows / flow_dr_mean)):
flows.append({"id": "f" + str(j), "data_rate": flow_dr_mean})
j += 1
source_list.append({
'node': ingress_nodes[i],
'vnf': "vnf_source",
'flows': flows
})
# Since the simulator right now does not have any link_dr , we are using a high value = 1000 for now.
first_result = bjointsp_place(os.path.abspath(args.network),
template,
source_list,
source_template_object=True,
cpu=node_cap,
mem=node_cap,
networkx=simulator.network,
write_result=False,
logging_level=None)
# creating the schedule and placement for the simulator from the first result file that BJointSP returns.
placement, schedule = get_placement_and_schedule(first_result, nodes_list,
sfc_name, sf_list)
# We run the simulator iterations number of times to get the Traffic info from the SimulatorAction object
# We generate new source file for the BJointSP from the traffic info we get from the simulator for each iteration
# Using this source file and the already generated Template file we call the 'place' fx of BJointSP
# In-case no source exists, we use the previous placement and schedule
for _ in tqdm(range(args.iterations)):
action = SimulatorAction(placement, schedule)
apply_state = simulator.apply(action)
source, source_exists = create_source_object(
apply_state.traffic, sf_list, sfc_name, ingress_nodes,
flow_dr_mean, processing_delay, flow_duration, run_duration)
if source_exists:
result = bjointsp_place(os.path.abspath(args.network),
template,
source,
source_template_object=True,
cpu=node_cap,
mem=node_cap,
networkx=simulator.network,
write_result=False,
logging_level=None)
placement, schedule = get_placement_and_schedule(
result, nodes_list, sfc_name, sf_list)
copy_input_files(results_dir, os.path.abspath(args.network),
os.path.abspath(args.service_functions),
os.path.abspath(args.config))
create_input_file(results_dir, len(ingress_nodes), "BJointSP-Fixed")
print(f"Saved results in {results_dir}")
def main():
args = parse_args()
timestamp = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
os.makedirs("logs", exist_ok=True)
logging.basicConfig(filename="logs/{}_{}_{}.log".format(os.path.basename(args.network),
timestamp, args.seed), level=logging.INFO)
logging.getLogger("coordsim").setLevel(logging.WARNING)
logging.getLogger("bjointsp").setLevel(logging.INFO)
# creating the simulator
# initializing the simulator with absolute paths to the network, service_functions and the config. files.
simulator = Simulator(os.path.abspath(args.network),
os.path.abspath(args.service_functions),
os.path.abspath(args.config), test_mode=True)
init_state = simulator.init(args.seed)
log.info("Network Stats after init(): %s", init_state.network_stats)
# assuming for now that there is only one SFC.
sfc_name = list(init_state.sfcs.keys())[0]
sf_list = list(init_state.sfcs.get(sfc_name))
sf_delays_dict = init_state.service_functions
nodes_list = [node['id'] for node in init_state.network.get('nodes')]
ingress_nodes, node_cap = get_ingress_nodes_and_cap(simulator.network)
# Getting the Mean Flow Data rate from the sim_config.yaml file
with open(args.config, "r") as f:
conf = yaml.load(f, yaml.SafeLoader)
flow_dr_mean = conf.get('flow_dr_mean')
# The template file is fixed, so it is created just once and used throughout for the 'place' fx of BJointSP
template = create_template(sfc_name, sf_list, sf_delays_dict)
# Since after the init() call to Simulator we don't get any traffic info back
# we can't create the source file needed for 'place' function of BJointSP,
# So we for just the first 'place' call to BJointSP create a source file with just ingress nodes having *
# *vnf_source as the vnf in it and date_rate of flow_dr_mean from the config file
with open(BJOINTSP_FIRST_SRC_LOCATION, "w") as f:
source_list = []
for i in range(len(ingress_nodes)):
source_list.append({'node': ingress_nodes[i], 'vnf': "vnf_source", 'flows': [{"id": "f" + str(i + 1),
"data_rate": flow_dr_mean}
]})
yaml.safe_dump(source_list, f, default_flow_style=False)
# Since the simulator right now does not have any link_dr , we are using a high value = 1000 for now.
first_result = bjointsp_place(os.path.abspath(args.network),
os.path.abspath(template),
os.path.abspath(BJOINTSP_FIRST_SRC_LOCATION), cpu=node_cap, mem=node_cap, dr=1000,
networkx=simulator.network)
# creating the schedule and placement for the simulator from the first result file that BJointSP returns.
placement, schedule = get_placement_and_schedule(os.path.abspath(first_result), nodes_list, sfc_name, sf_list)
# We run the simulator iterations number of times to get the Traffic info from the SimulatorAction object
# We generate new source file for the BJointSP from the traffic info we get from the simulator for each iteration
# Using this source file and the already generated Template file we call the 'place' fx of BJointSP
# Incase no source exists, we use the previous placement and schedule
for i in range(args.iterations):
action = SimulatorAction(placement, schedule)
apply_state = simulator.apply(action)
log.info("Network Stats after apply() # %s: %s", i + 1, apply_state.network_stats)
source, source_exists = create_source_file(apply_state.traffic, sf_list, sfc_name, flow_dr_mean)
if source_exists:
result = bjointsp_place(os.path.abspath(args.network), os.path.abspath(template), os.path.abspath(source),
cpu=node_cap, mem=node_cap, dr=1000, networkx=simulator.network)
placement, schedule = get_placement_and_schedule(os.path.abspath(result), nodes_list, sfc_name, sf_list)
simulator.params.adapter.writer.write_results(simulator.params.adapter.metrics.metrics)
# 'output_path': f'out/{network}'
# }
# Evaluation params
network = 'dfn_58.graphml'
args = {
'network': f'../../../params/networks/{network}',
'service_functions': '../../../params/services/3sfcs.yaml',
'config': '../../../params/config/hc_0.5.yaml',
'seed': 155,
'output_path': f'out/{network}'
}
# Setup logging to screen
logging.basicConfig(level=logging.INFO)
logging.getLogger('bjointsp').setLevel(logging.WARNING)
logging.getLogger('coordsim').setLevel(logging.INFO)
logging.getLogger('coordsim.reader').setLevel(logging.WARNING)
simulator = Simulator(test_mode=True)
# Setup algorithm
algo = BJointSPAlgo(simulator,
recalc_before_drop=True,
logging_level=logging.INFO)
algo.init(os.path.abspath(args['network']),
os.path.abspath(args['service_functions']),
os.path.abspath(args['config']), args['seed'],
args['output_path'])
# Execute orchestrated simulation
algo.run()