def figure2a_line_2_bgpsec_partial(
nx_graph: nx.Graph, deployment: int,
trials: List[Tuple[AS_ID, AS_ID]]) -> List[Fraction]:
graph = ASGraph(nx_graph, policy=RPKIPolicy())
for asys in graph.identify_top_isps(deployment):
asys.policy = BGPsecMedSecPolicy()
return figure2a_experiment(graph, trials, n_hops=1)
def figure9_line_1_rpki_partial(
nx_graph: nx.Graph, deployment: int,
trials: List[Tuple[AS_ID, AS_ID]]) -> List[Fraction]:
graph = ASGraph(nx_graph, policy=DefaultPolicy())
for asys in graph.identify_top_isps(deployment):
asys.policy = RPKIPolicy()
return figure2a_experiment(graph, trials, n_hops=0)
def figure2a_line_1_next_as(
nx_graph: nx.Graph, deployment: int,
trials: List[Tuple[AS_ID, AS_ID]]) -> List[Fraction]:
graph = ASGraph(nx_graph, policy=RPKIPolicy())
for asys in graph.identify_top_isps(deployment):
asys.policy = PathEndValidationPolicy()
return figure2a_experiment(graph, trials, n_hops=1)
def figure8_line_2_bgpsec_partial(
nx_graph: nx.Graph, deployment: int, p: float,
trials: List[Tuple[AS_ID, AS_ID]]) -> List[Fraction]:
results = []
for _ in range(20):
graph = ASGraph(nx_graph, policy=RPKIPolicy())
for asys in graph.identify_top_isps(int(deployment / p)):
if random.random() < p:
asys.policy = BGPsecMedSecPolicy()
results.extend(figure2a_experiment(graph, trials, n_hops=1))
return results
def figure2a_line_4_rpki(nx_graph: nx.Graph,
trials: List[Tuple[AS_ID, AS_ID]]) -> List[Fraction]:
graph = ASGraph(nx_graph, policy=RPKIPolicy())
return figure2a_experiment(graph, trials, n_hops=1)