def smallworld(n, rewire=0.3, seed=35):
"""Return a watts-strogatz small world graph.
Mimics the layout of smallworld_topo.SmallWorldTopology.
"""
graph = nx.connected_watts_strogatz_graph(n, min(4, n/3), rewire, seed=seed)
return from_graph(graph)
def waxman(n, alpha=0.8, beta=0.1):
"""Return a waxman random graph with n nodes.
alpha increases edge probability, beta increases long edge probability.
"""
import waxman_topo
return from_graph(waxman_topo.waxman_graph(n, alpha, beta))
def linear_hosts(*linear_nodes):
"""Returns topo, [(slice, policy)]"""
topo = nxtopo.from_graph(nx.path_graph(4))
nodes = [set(ns) for ns in linear_nodes]
for n in topo.nodes():
h1 = 100 + n*10 + 1
h2 = 100 + n*10 + 2
topo.add_host(h1)
topo.add_host(h2)
topo.add_link(n, h1)
topo.add_link(n, h2)
for ns in nodes:
if n in ns:
ns.update([h1, h2])
topo.finalize()
edge_policies = []
for ns in linear_nodes:
predicates = {}
for n in ns:
h1 = 100 + n*10 + 1
h2 = 100 + n*10 + 2
h1_port = topo.node[h1]['port'][0]
h2_port = topo.node[h2]['port'][0]
predicates[h1_port] = nc.Top()
predicates[h2_port] = nc.Top()
edge_policies.append(predicates)
topos = [topo.subgraph(ns) for ns in nodes]
slices = [slicing.ident_map_slice(t, pol)
for t, pol in zip(topos, edge_policies)]
combined = zip(slices, [policy_gen.flood_observe(t) for t in topos])
return (topo, combined)
def linear_all_ports(*linear_nodes):
"""Linear graph on four nodes with reflexive forwarding."""
topo = nxtopo.from_graph(nx.path_graph(4))
topo.finalize()
topos = [topo.subgraph(nodes) for nodes in linear_nodes]
policies = [policy_gen.flood_observe(t, all_ports=True) for t in topos]
return topo, policies
def linear(*linear_nodes):
"""Linear graph on four nodes, slices from input."""
topo = nxtopo.from_graph(nx.path_graph(4))
topo.finalize()
topos = [topo.subgraph(nodes) for nodes in linear_nodes]
policies = [policy_gen.flood_observe(t) for t in topos]
return topo, policies
def k4():
"""K4 complete graph."""
topo = nxtopo.from_graph(nx.complete_graph(4))
topo.finalize()
topos = [topo.subgraph(nodes) for nodes in k4_nodes]
edge_policies = [{} for t in topos]
slices = [slicing.ident_map_slice(t, pol)
for t, pol in zip(topos, edge_policies)]
combined = zip(slices, [policy_gen.flood_observe(t) for t in topos])
return (topo, combined)
