def best_fit_run(physical_graph,
requests,
save=True,
load=2000,
max_time=500,
verbose=True):
physical_best_fit = physical_graph.copy()
request_graphs_best_fit = [r.copy() for r in requests]
results = get_run_result(physical_best_fit,
request_graphs_best_fit,
method="bestFit",
traffic_load=load,
max_time=max_time,
cost_revenue=True,
utils=True,
verbose=verbose)
if save:
save_results('bf', results)
return results
def neuroViNE_run(physical_graph,
requests,
save=True,
load=2000,
max_time=500,
verbose=True):
physical_neuro = physical_graph.copy()
request_graphs_neuro = [r.copy() for r in requests]
results = get_run_result(physical_neuro,
request_graphs_neuro,
method="neuroViNE",
traffic_load=load,
max_time=max_time,
cost_revenue=True,
utils=True,
verbose=verbose)
if save:
save_results('nv', results)
return results
def grc_run(physical_graph,
requests,
save=True,
load=2000,
max_time=500,
verbose=True):
physical_grc = physical_graph.copy()
request_graphs_grc = [r.copy() for r in requests]
results = get_run_result(physical_grc,
request_graphs_grc,
method="grc",
traffic_load=load,
max_time=max_time,
cost_revenue=True,
utils=True,
verbose=verbose)
if save:
save_results('grc', results)
return results
def graphViNE_run(physical_graph,
requests,
save=True,
load=2000,
max_time=500,
verbose=True,
n_clusters=4):
physical_graph_vine = physical_graph.copy()
request_graphs_graph_vine = [r.copy() for r in requests]
results = get_run_result(physical_graph_vine,
request_graphs_graph_vine,
method="graphViNE",
traffic_load=load,
max_time=max_time,
cost_revenue=True,
utils=True,
verbose=verbose,
n_clusters=n_clusters)
if save:
save_results(f'gv{n_clusters}', results)
return results