def OS3EWeightedGraph():
data = {}
g = OS3EGraph()
longit = {}
lat = {}
# Get locations
if os.path.isfile(LATLONG_FILE):
print "Using existing lat/long file"
data = read_json_file(LATLONG_FILE)
else:
print "Generating new lat/long file"
for n in g.nodes():
data[n] = get_lat_long(n)
write_json_file(LATLONG_FILE, data)
for node in g.nodes():
latit = float(data[node]["Latitude"])
lon = float(data[node]["Longitude"])
lat[node] = latit
longit[node] = lon
nx.set_node_attributes(g,'Latitude',lat)
nx.set_node_attributes(g,'Longitude',longit)
# Append weights
for src, dst in g.edges():
g[src][dst]["weight"] = dist_in_miles(data, src, dst)
#print "%s to %s: %s" % (src, dst, g[src][dst]["weight"])
return g
def test_latency_bound(self):
'''Ensure fraction of nodes within bound is reasonable.'''
g = OS3EGraph()
g_unit = set_unit_weights(g.copy())
apsp = dict(nx.all_pairs_shortest_path_length(g))
apsp_paths = dict(nx.all_pairs_shortest_path(g))
path_lens = []
for a in apsp:
for b in apsp:
path_lens.append(apsp[a][b])
max_path_len = max(path_lens)
combos = [["Sunnyvale, CA", "Boston"], ["Portland"],
["Sunnyvale, CA", "Salt Lake City"], ["Seattle", "Boston"],
["Seattle", "Portland"]]
for combo in combos:
one = fraction_within_latency(g, combo, apsp, max_path_len + 1.0)
self.assertEqual(one, 1.0)
two = fraction_within_latency(g, combo, apsp, 0.000001)
self.assertEqual(two, len(combo) / float(g.number_of_nodes()))
def test_os3e_weighted(self):
'''Ensure unit-weighted version of graph yields same availability.'''
link_fail_prob = 0.01
g = OS3EGraph()
g_unit = set_unit_weights(g.copy())
apsp = nx.all_pairs_shortest_path_length(g)
apsp_paths = nx.all_pairs_shortest_path(g)
combos = [["Sunnyvale, CA", "Boston"],
["Portland"],
["Sunnyvale, CA", "Salt Lake City"],
["Seattle", "Boston"],
["Seattle", "Portland"]]
for combo in combos:
for max_failures in range(1, 2):
a, c = availability_one_combo(g, combo, apsp, apsp_paths,
False, link_fail_prob, max_failures)
a_u, c_u = availability_one_combo(g_unit, combo, apsp,
apsp_paths, True, link_fail_prob, max_failures)
self.assertAlmostEqual(a, a_u)
self.assertAlmostEqual(c, c_u)
def OS3EWeightedGraph():
data = {}
g = OS3EGraph()
# Get locations
if os.path.isfile(LATLONG_FILE):
print("Using existing lat/long file")
data = read_json_file(LATLONG_FILE)
else:
print("Generating new lat/long file")
for n in g.nodes():
data[n] = get_lat_long(n)
write_json_file(LATLONG_FILE, data)
# Append weights
for src, dst in g.edges():
g[src][dst]["weight"] = dist_in_miles(data, src, dst)
#print "%s to %s: %s" % (src, dst, g[src][dst]["weight"])
return g
#!/usr/bin/env python import cc from topo.os3e import OS3EGraph g = OS3EGraph() link_fail_prob = 0.01 print "OS3E" print "sssp: %03f" % cc.compute(g, link_fail_prob, 0, 1, 'sssp') print "any: %03f" % cc.compute(g, link_fail_prob, 0, 1, 'any')
def test_os3e(self):
'''Validate coverage and availability are reasonable.'''
link_fail_prob = 0.01
g = OS3EGraph()
apsp = nx.all_pairs_shortest_path_length(g)
apsp_paths = nx.all_pairs_shortest_path(g)
combos = [["Sunnyvale, CA", "Boston"],
["Portland"],
["Sunnyvale, CA", "Salt Lake City"],
["Seattle", "Boston"],
["Seattle", "Portland"]]
weighted = False
'''
34 nodes
41 edges
pfail = 0.01
p(good) =
1 * p(success) * p(success) * ... 41 = 0.99 ** 41 =
0.66228204098398347
p(1 fail) =
(41 choose 1) * (p(success) ** (41 - 1)) * p(fail) =
41 * (0.99 ** 40) * 0.01 =
0.27427842101356892
p(2 fail) =
(41 choose 2) * (p(success) ** (41 - 2)) * (p(fail) ** 2) =
820 * (0.99 ** 39) * (0.01 ** 2) =
0.055409782022943221
p(3 fail) =
(41 choose 3) * (p(success) ** (41 - 2)) * (p(fail) ** 2) =
10660 * (0.99 ** 38) * (0.01 ** 3) =
0.0072760319828107265
sum (0..1 failures) =
0.66228204098398347 + 0.27427842101356892 =
0.93656046199755238
error bar =
0.063439538002447615
sum (0..2 failures) =
0.66228204098398347 + 0.27427842101356892 + 0.055409782022943221 =
0.99197024402049561
error bar =
0.00802
sum (0..3 failures) =
0.66228204098398347 + 0.27427842101356892 + 0.055409782022943221 +
0.0072760319828107265 =
0.99924627600330629
error bar = 0.00075
'''
exp_coverage = {
0: 0.66228204098398347,
1: 0.27427842101356892,
2: 0.055409782022943221,
3: 0.0072760319828107265
}
def get_coverage(f):
'''Return expected coverage for given number of failures.'''
return sum([v for k, v in exp_coverage.iteritems() if k <= f])
for combo in combos:
for max_failures in range(3):
a, c = availability_one_combo(g, combo, apsp, apsp_paths,
weighted, link_fail_prob,
max_failures)
self.assertTrue(a < 1.0)
self.assertTrue(c < 1.0)
self.assertAlmostEqual(get_coverage(max_failures), c)