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