def UMMP_time_dummy():
size = [20, 30, 40]
times = []
for s in size:
ufuncs = utility.read_ufuncs("../data/ufuncs/uf_" + str(s * (s - 1)) +
".txt")
scaled_ufuncs = utility.scale_ufuncs(ufuncs)
pl_mat, cms, c = topo.read_data("../data/topologies/waxman_" + str(s) +
"_3_" + str(s * (s - 1)) + ".txt")
new_c = [10000.0 for i in range(len(c))]
c = new_c
pl_mat = np.matrix(pl_mat)
start_time = time.time()
cm_alloc, paths_alloc, useful_when_error = UMMP.max_min_program(
pl_mat, cms, c, scaled_ufuncs, len(cms))
tot_time = time.time() - start_time
times.append(tot_time)
print(times)
def congestion_time():
caps = [4000.0, 6000.0, 8000.0, 10000.0]
times = []
for cap in caps:
time_sum = 0
for i in range(1, 11):
ufuncs = utility.read_ufuncs("../data/ufuncs/uf_870" + "_v" +
str(i) + ".txt")
scaled_ufuncs = utility.scale_ufuncs(ufuncs)
pl_mat, cms, c = topo.read_data(
"../data/topologies/waxman_30_3_870.txt")
new_c = [cap for i in range(len(c))]
c = new_c
pl_mat = np.matrix(pl_mat)
start_time = time.time()
#cm_alloc, paths_alloc, useful_when_error = UMMP.max_min_program(
# pl_mat, cms, c, scaled_ufuncs, len(cms))
#initial_splits=UIEWF.exp_congestion_decay_splits(cms,pl_mat)
#cm_alloc,diffs=UIEWF.Util_IEWF(
# pl_mat,cms,c,initial_splits,scaled_ufuncs,it=100,th=0.03)
cm_alloc, diffs = Hybrid.hybrid_alloc(pl_mat,
cms,
c,
scaled_ufuncs,
it=100,
th=0.03,
k=0.5 * len(cms))
tot_time = time.time() - start_time
time_sum += tot_time
avg_time = time_sum / 10
times.append(avg_time)
print(times)
def performance_waxman():
plt.rcParams['font.family'] = 'serif'
plt.rcParams['font.size'] = 18
plt.rcParams['font.weight'] = 'bold'
plt.rcParams['axes.labelweight'] = 'bold'
plt.rcParams['axes.labelsize'] = 18
fig, ax = plt.subplots()
fig.subplots_adjust(left=0.16, top=0.995, bottom=0.13, right=0.995)
pl_mat, cms, c = topo.read_data('../data/topologies/waxman_30_3_870.txt')
ufuncs = utility.read_ufuncs("../data/ufuncs/uf_870_v4.txt")
scaled_ufuncs = utility.scale_ufuncs(ufuncs)
new_c = [4000.0 for i in range(len(c))]
c = new_c
pl_mat = np.matrix(pl_mat)
x = [i for i in range(0, 870)]
cm_alloc, paths_alloc, useful_when_error = UMMP.max_min_program(
pl_mat, cms, c, scaled_ufuncs, len(cms))
util_alloc = utility.flow2util(ufuncs, cm_alloc)
ax.plot(x, sorted(util_alloc), label='Optimal', linestyle='solid')
#initial_splits=UIEWF.exp_congestion_decay_splits(cms,pl_mat)
#cm_alloc,diffs=UIEWF.Util_IEWF(pl_mat,cms,c,initial_splits,scaled_ufuncs,it=20,th=0.001)
#util_alloc=utility.flow2util(ufuncs,cm_alloc)
#ax.plot(x,sorted(util_alloc),label='U-IEWF',linestyle='dotted')
#cm_alloc,diffs=Hybrid.hybrid_alloc(pl_mat,cms,c,scaled_ufuncs,it=20,th=0.001,k=100)
#util_alloc=utility.flow2util(ufuncs,cm_alloc)
#ax.plot(x,sorted(util_alloc),label='Hybrid-100',linestyle='dashed')
ax.set_xticks(np.arange(0, 871, step=100))
ax.set_ylabel('Utility')
ax.set_xlabel('Commodity Index')
#ax.grid(ls='--')
ax.legend()
plt.show()
def dummy():
# running_time()
pl_mat, cms, c = topo.read_data('../data/topologies/waxman_30_2_870.txt')
ufuncs = utility.read_ufuncs("../data/ufuncs/uf_870.txt")
scaled_ufuncs = utility.scale_ufuncs(ufuncs)
new_c = [10000.0 for i in range(len(c))]
c = new_c
pl_mat = np.matrix(pl_mat)
start_time = time.time()
cm_alloc, paths_alloc, useful_when_error = UMMP.max_min_program(
pl_mat, cms, c, scaled_ufuncs, len(cms))
tot_time_1 = time.time() - start_time
#print("UMMP total time is "+str(tot_time))
start_time = time.time()
initial_splits = UIEWF.exp_congestion_decay_splits(cms, pl_mat)
cm_alloc, diffs = UIEWF.Util_IEWF(pl_mat,
cms,
c,
initial_splits,
scaled_ufuncs,
it=10,
th=0.03)
tot_time_2 = time.time() - start_time
#print("UIEWF total time is "+str(tot_time))
start_time = time.time()
cm_alloc, diffs = Hybrid.hybrid_alloc(pl_mat,
cms,
c,
scaled_ufuncs,
it=10,
th=0.03,
k=500)
tot_time_3 = time.time() - start_time
#print("Hybrid total time is "+str(tot_time))
print("UMMP total time is " + str(tot_time_1))
print("UIEWF total time is " + str(tot_time_2))
print("Hybrid total time is " + str(tot_time_3))
def UIEWF_time():
size = [20, 30, 40]
times = []
for s in size:
time_sum = 0
for i in range(1, 11):
ufuncs = utility.read_ufuncs("../data/ufuncs/uf_" + str(s *
(s - 1)) +
"_v" + str(i) + ".txt")
scaled_ufuncs = utility.scale_ufuncs(ufuncs)
pl_mat, cms, c = topo.read_data("../data/topologies/waxman_" +
str(s) + "_3_" + str(s * (s - 1)) +
".txt")
new_c = [10000.0 for i in range(len(c))]
c = new_c
pl_mat = np.matrix(pl_mat)
start_time = time.time()
initial_splits = UIEWF.exp_congestion_decay_splits(cms, pl_mat)
cm_alloc, diffs = UIEWF.Util_IEWF(pl_mat,
cms,
c,
initial_splits,
scaled_ufuncs,
it=100,
th=0.03)
tot_time = time.time() - start_time
time_sum += tot_time
avg_time = time_sum / 10
times.append(avg_time)
print(times)
def Hybrid_time():
size = [40]
times = []
for s in size:
time_sum = 0
for i in range(1, 11):
ufuncs = utility.read_ufuncs("../data/ufuncs/uf_" + str(s *
(s - 1)) +
"_v" + str(i) + ".txt")
scaled_ufuncs = utility.scale_ufuncs(ufuncs)
pl_mat, cms, c = topo.read_data("../data/topologies/waxman_" +
str(s) + "_3_" + str(s * (s - 1)) +
".txt")
new_c = [10000.0 for i in range(len(c))]
c = new_c
pl_mat = np.matrix(pl_mat)
start_time = time.time()
cm_alloc, diffs = Hybrid.hybrid_alloc(pl_mat,
cms,
c,
scaled_ufuncs,
it=100,
th=0.03,
k=0.2 * len(cms))
tot_time = time.time() - start_time
time_sum += tot_time
avg_time = time_sum / 10
times.append(avg_time)
print(times)
def abilene_time():
time_sum = 0
for i in range(1, 11):
ufuncs = utility.read_ufuncs("../data/ufuncs/uf_110" + "_v" + str(i) +
".txt")
scaled_ufuncs = utility.scale_ufuncs(ufuncs)
pl_mat, cms, c = topo.read_data("../data/topologies/abilene_2_110.txt")
new_c = [10000.0 for i in range(len(c))]
c = new_c
pl_mat = np.matrix(pl_mat)
start_time = time.time()
#cm_alloc, paths_alloc, useful_when_error = UMMP.max_min_program(
# pl_mat, cms, c, scaled_ufuncs, len(cms))
#initial_splits=UIEWF.exp_congestion_decay_splits(cms,pl_mat)
#cm_alloc,diffs=UIEWF.Util_IEWF(
# pl_mat,cms,c,initial_splits,scaled_ufuncs,it=100,th=0.03)
cm_alloc, diffs = Hybrid.hybrid_alloc(pl_mat,
cms,
c,
scaled_ufuncs,
it=100,
th=0.03,
k=0.2 * len(cms))
tot_time = time.time() - start_time
time_sum += tot_time
avg_time = time_sum / 10
print("average time is")
print(avg_time)
def convergence_waxman_size():
plt.rcParams['font.family'] = 'serif'
plt.rcParams['font.size'] = 18
plt.rcParams['font.weight'] = 'bold'
plt.rcParams['axes.labelweight'] = 'bold'
plt.rcParams['axes.labelsize'] = 18
fig, ax = plt.subplots()
fig.subplots_adjust(left=0.16, top=0.995, bottom=0.13, right=0.995)
size = [20, 30]
markers = ['x', 'v', '.', '^']
x = [i for i in range(2, 21)]
for i in range(len(size)):
s = size[i]
ufuncs = utility.read_ufuncs("../data/ufuncs/uf_" + str(s * (s - 1)) +
".txt")
pl_mat, cms, c = topo.read_data("../data/topologies/waxman_" + str(s) +
"_3_" + str(s * (s - 1)) + ".txt")
ufuncs = utility.scale_ufuncs(ufuncs)
new_c = [10000.0 for i in range(len(c))]
c = new_c
pl_mat = np.matrix(pl_mat)
initial_splits = UIEWF.exp_decay_splits(cms, pl_mat)
cm_alloc, diffs = UIEWF.Util_IEWF(pl_mat,
cms,
c,
initial_splits,
ufuncs,
it=20,
th=0.00001)
ax.plot(x,
diffs,
label='len_decay',
marker=markers[i],
linestyle='dotted')
initial_splits = UIEWF.exp_congestion_decay_splits(cms, pl_mat)
cm_alloc, diffs = UIEWF.Util_IEWF(pl_mat,
cms,
c,
initial_splits,
ufuncs,
it=20,
th=0.00001)
ax.plot(x,
diffs,
label="waxman-" + str(s),
marker=markers[i],
linestyle='solid')
ax.set_xticks(np.arange(2, 21, step=2))
ax.set_ylabel('Difference')
ax.set_xlabel('Iteration number')
ax.grid(ls='--')
ax.legend()
plt.show()
def convergence_abilene():
plt.rcParams['font.family'] = 'serif'
plt.rcParams['font.size'] = 18
plt.rcParams['font.weight'] = 'bold'
plt.rcParams['axes.labelweight'] = 'bold'
plt.rcParams['axes.labelsize'] = 18
fig, ax = plt.subplots()
fig.subplots_adjust(left=0.16, top=0.995, bottom=0.13, right=0.995)
ufuncs = utility.read_ufuncs("../data/ufuncs/uf_110.txt")
pl_mat, cms, c = topo.read_data('../data/topologies/abilene_2_110.txt')
ufuncs = utility.scale_ufuncs(ufuncs)
new_c = [10000.0 for i in range(len(c))]
c = new_c
pl_mat = np.matrix(pl_mat)
initial_splits = UIEWF.uniform_splits(cms)
cm_alloc, diffs = UIEWF.Util_IEWF(pl_mat,
cms,
c,
initial_splits,
ufuncs,
it=20,
th=0.00001)
x = [i for i in range(21)][2:]
ax.plot(x, diffs, label='uniform', marker='x', linestyle='solid')
initial_splits = UIEWF.random_splits(cms)
cm_alloc, diffs = UIEWF.Util_IEWF(pl_mat,
cms,
c,
initial_splits,
ufuncs,
it=20,
th=0.00001)
ax.plot(x, diffs, label='random', marker='v', linestyle='solid')
initial_splits = UIEWF.exp_decay_splits(cms, pl_mat)
cm_alloc, diffs = UIEWF.Util_IEWF(pl_mat,
cms,
c,
initial_splits,
ufuncs,
it=20,
th=0.00001)
ax.plot(x, diffs, label='len_decay', marker='.', linestyle='solid')
initial_splits = UIEWF.exp_congestion_decay_splits(cms, pl_mat)
cm_alloc, diffs = UIEWF.Util_IEWF(pl_mat,
cms,
c,
initial_splits,
ufuncs,
it=20,
th=0.00001)
ax.plot(x, diffs, label='congestion_decay', marker='^', linestyle='solid')
ax.set_xticks(np.arange(2, 21, step=2))
ax.set_yticks(np.arange(0.0, 0.13, step=0.02))
ax.set_ylabel('Difference')
ax.set_xlabel('Iteration number')
ax.grid(ls='--')
ax.legend()
plt.show()
