def get_nfv_distribution(ratio, host_num, file_path):
CODEC = 'utf-8'
mynet = "8s9vnf.json"
g = DiGraph(mynet)
#自定义VNF的处理能力（1-10）
capacity = {
'F1': 10,
'F2': 10,
'F3': 10,
'I1': 10,
'I2': 10,
'I3': 10,
'P1': 10,
'P2': 10,
'P3': 10
}
each_NF_num = 3
#the number of 80 hosts
flowDic = get_flows(host_num, ratio)
flow_number = len(flowDic)
print "flow_number", flow_number
#Find out which streams of each type of NF have passed
flow = {}
flow['F'] = []
flow['I'] = []
flow['P'] = []
for key in flowDic:
if 'F' in str(flowDic[key][3]):
flow['F'].append(key)
if 'I' in str(flowDic[key][3]):
flow['I'].append(key)
if 'P' in str(flowDic[key][3]):
flow['P'].append(key)
#j stands for 9 processors, i stands for task (flow)
p = [([0] * len(flow) * 3) for i in range(len(flowDic))]
for j in capacity.keys():
#compute Pij= brand*distance(S-VNF-D) / processors
if 'F' in j:
if '1' in j:
row = 0
elif '2' in j:
row = 1
elif '3' in j:
row = 2
for i in flow['F']:
#src,vnf,dst
# print flowDic[i][0],j,flowDic[i][1]
path1 = dijkstra(g, flowDic[i][0], j)
path2 = dijkstra(g, j, flowDic[i][1])
distance = path1.get('cost') + path2.get('cost')
bandwidth = flowDic[int(i)][2]
power = capacity[j]
#print power
p[i - 1][row] = bandwidth * distance / power
#print i
#print p[i-1][row]
elif 'I' in j:
if '1' in j:
row = 3
elif '2' in j:
row = 4
elif '3' in j:
row = 5
for i in flow['I']:
#print flowDic[i][0],j,flowDic[i][1]
path1 = dijkstra(g, flowDic[i][0], j)
path2 = dijkstra(g, j, flowDic[i][1])
distance = path1.get('cost') + path2.get('cost')
bandwidth = flowDic[int(i)][2]
power = capacity[j]
#print power
p[i - 1][row] = bandwidth * distance / power
#print i
#print p[i-1][row]
elif 'P' in j:
if '1' in j:
row = 6
elif '2' in j:
row = 7
elif '3' in j:
row = 8
for i in flow['P']:
#print flowDic[i][0],j,flowDic[i][1]
path1 = dijkstra(g, flowDic[i][0], j)
path2 = dijkstra(g, j, flowDic[i][1])
distance = path1.get('cost') + path2.get('cost')
bandwidth = flowDic[int(i)][2]
power = capacity[j]
#print power
p[i - 1][row] = bandwidth * distance / power
#print i
#print p[i-1][row]
print "p", p
'''
Solving linear equation
'''
#x[i][j] ：Indicates that the ith stream passes through the jth vnf, and j(0-8) represents [F1, F2, F3, I1, I2, I3, P1, P2, P3]
'''Which F passed'''
x = [[0 for col in range(3)] for row in range(len(flowDic))]
#print x
for i in range(0, len(flowDic)):
for j in range(0, 3):
x[i][j] = "x"
if len(flowDic) < 100000:
if i < 10:
x[i][j] = x[i][j] + "0000"
elif i < 100:
x[i][j] = x[i][j] + "000"
elif i < 1000:
x[i][j] = x[i][j] + "00"
elif i < 10000:
x[i][j] = x[i][j] + "0"
x[i][j] = x[i][j] + str(i) + str(j)
z = []
for i in range(0, len(flowDic)):
z.append("z" + str(i))
temp = []
for i in range(0, len(flowDic)):
for j in range(0,
3): # 3 si the number of path that each flow can choose
temp.append(x[i][j])
for i in range(0, len(flowDic)):
temp.append(z[i])
prob = LpProblem('lptest', LpMinimize)
r = LpVariable('r', lowBound=0)
xx = LpVariable.dicts("", temp, lowBound=0,
upBound=1) #,cat = pulp.LpInteger
print x[0]
#Add target equation
prob += r
#0->F(0,1,2);1->I(3,4,5);2->P(6,7,8)
x_e = defaultdict(lambda: (defaultdict(lambda:
(defaultdict(lambda: None)))))
for i in range(3):
for j in range(len(flowDic)):
x_e[i][j][0] = x[j][i]
x_e[i][j][1] = p[j][i]
for i in range(0, 3):
prob += lpSum(xx[x_e[i][j][0]] * x_e[i][j][1] for j in x_e[i]) <= r
#Add constraints
for i in range(0, len(flowDic)):
prob += lpSum([xx[j] for j in x[i]]) == 1
#solve the question
GLPK().solve(prob)
print 'objective_sr =', value(prob.objective)
i = 0
j = 0
l = 0
for v in prob.variables():
l = l + 1
if l < flow_number * 3 + 1: #(the number of flows /cdot 3) +1
x[i][j] = v.varValue
if j < 2:
j = j + 1
else:
i = i + 1
j = 0
for i in range(0, flow_number):
k = 0
choose = 0
for j in range(0, 3):
if x[i][j] >= k:
choose = j
k = x[i][j]
for j in range(0, 3):
if j == choose:
x[i][j] = 1
else:
x[i][j] = 0
for i in range(0, flow_number):
if ('F' in str(flowDic[i + 1][3])):
for j in range(0, 3):
if x[i][j] == 1:
flowDic[i + 1].append(j)
'''which I'''
p_1 = [([0] * 3) for i in range(len(flowDic))]
for i in range(len(flowDic)):
for j in range(3):
p_1[i][j] = p[i][j + 3]
x1 = [[0 for col in range(3)] for row in range(len(flowDic))]
for i in range(0, len(flowDic)):
for j in range(0, 3):
x1[i][j] = "x"
if len(flowDic) < 100000:
if i < 10:
x1[i][j] = x1[i][j] + "0000"
elif i < 100:
x1[i][j] = x1[i][j] + "000"
elif i < 1000:
x1[i][j] = x1[i][j] + "00"
elif i < 10000:
x1[i][j] = x1[i][j] + "0"
x1[i][j] = x1[i][j] + str(i) + str(j)
z1 = []
for i in range(0, len(flowDic)):
z1.append("z" + str(i))
temp1 = []
for i in range(0, len(flowDic)):
for j in range(0,
3): # 3 si the number of path that each flow can choose
temp1.append(x1[i][j])
for i in range(0, len(flowDic)):
temp1.append(z1[i])
prob1 = LpProblem('lptest1', LpMinimize)
r1 = LpVariable('r1', lowBound=0)
xx1 = LpVariable.dicts("", temp1, lowBound=0,
upBound=1) #, cat = pulp.LpInteger
prob1 += r1
#0->F(0,1,2);1->I(3,4,5);2->P(6,7,8)
x_e1 = defaultdict(lambda: (defaultdict(lambda:
(defaultdict(lambda: None)))))
for i in range(3):
for j in range(len(flowDic)):
x_e1[i][j][0] = x1[j][i]
x_e1[i][j][1] = p_1[j][i]
for i in range(0, 3):
prob1 += lpSum(xx1[x_e1[i][j][0]] * x_e1[i][j][1]
for j in x_e1[i]) <= r1
for i in range(0, len(flowDic)):
prob1 += lpSum([xx1[j] for j in x1[i]]) == 1
GLPK().solve(prob1)
print 'objective_sr =', value(prob1.objective)
i = 0
j = 0
l = 0
for v in prob1.variables():
l = l + 1
if l < flow_number * 3 + 1: #(the number of flows /cdot 3) +1
x[i][j] = v.varValue
if j < 2:
j = j + 1
else:
i = i + 1
j = 0
for i in range(0, flow_number):
k = 0
choose = 0
for j in range(0, 3):
if x[i][j] >= k:
choose = j
k = x[i][j]
for j in range(0, 3):
if j == choose:
x[i][j] = 1
else:
x[i][j] = 0
for i in range(0, flow_number):
if ('I' in str(flowDic[i + 1][3])):
for j in range(0, 3):
if x[i][j] == 1:
flowDic[i + 1].append(j)
'''which P'''
p_3 = [([0] * 3) for i in range(len(flowDic))]
for i in range(len(flowDic)):
for j in range(3):
p_3[i][j] = p[i][j + 6]
print p_3
x3 = [[0 for col in range(3)] for row in range(len(flowDic))]
for i in range(0, len(flowDic)):
for j in range(0, 3):
x3[i][j] = "x"
if len(flowDic) < 100000:
if i < 10:
x3[i][j] = x3[i][j] + "0000"
elif i < 100:
x3[i][j] = x3[i][j] + "000"
elif i < 1000:
x3[i][j] = x3[i][j] + "00"
elif i < 10000:
x3[i][j] = x3[i][j] + "0"
x3[i][j] = x3[i][j] + str(i) + str(j)
z3 = []
for i in range(0, len(flowDic)):
z3.append("z3" + str(i))
temp3 = []
for i in range(0, len(flowDic)):
for j in range(0,
3): # 3 si the number of path that each flow can choose
temp3.append(x3[i][j])
for i in range(0, len(flowDic)):
temp3.append(z3[i])
prob3 = LpProblem('lptest3', LpMinimize)
r3 = LpVariable('r3', lowBound=0)
xx3 = LpVariable.dicts("", temp3, lowBound=0,
upBound=1) #, cat = pulp.LpInteger
prob3 += r3
x_e3 = defaultdict(lambda: (defaultdict(lambda:
(defaultdict(lambda: None)))))
for i in range(3):
for j in range(len(flowDic)):
x_e3[i][j][0] = x3[j][i]
x_e3[i][j][1] = p_3[j][i]
for i in range(0, 3):
prob3 += lpSum(xx3[x_e3[i][j][0]] * x_e3[i][j][1]
for j in x_e3[i]) <= r3
for i in range(0, len(flowDic)):
prob3 += lpSum([xx3[j] for j in x3[i]]) == 1
GLPK().solve(prob3)
print 'objective_sr =', value(prob3.objective)
i = 0
j = 0
l = 0
for v in prob3.variables():
l = l + 1
if l < flow_number * 3 + 1: #(the number of flows /cdot 3) +1
x[i][j] = v.varValue
if j < 2:
j = j + 1
else:
i = i + 1
j = 0
for i in range(0, flow_number):
k = 0
choose = 0
for j in range(0, 3):
if x[i][j] >= k:
choose = j
k = x[i][j]
for j in range(0, 3):
if j == choose:
x[i][j] = 1
else:
x[i][j] = 0
for i in range(0, flow_number):
if ('P' in str(flowDic[i + 1][3])):
for j in range(0, 3):
if x[i][j] == 1:
flowDic[i + 1].append(j)
#print flowDic[i+1]
flow_vnf = file_path + '/flow_vnf.txt'
file = open(flow_vnf, 'w')
NF_load = (defaultdict(lambda: None))
for i in capacity:
NF_load[i] = 0
for t in flowDic:
line = str(flowDic[t])
newsDate = txt_wrap_by("'", "'", line, 0)
flow_rate = txt_wrap_by2(",", ",", line)[1]
#print "flow-rate",flow_rate
nf_number = [] #Save the serial number of each passed NF
h = txt_wrap_by2(",", ",", line)
for i in range(3, len(h)):
nf_number.append(h[i])
ff = find_n_sub_str(line, ",", 3, 0)
sfc_len = (len(newsDate[2]) + 1) / 2
k = find_n_sub_str(line, ",", 2 + sfc_len,
0) # Find the index where the last comma is located
nf_number.append(txt_wrap_by(",", "]", line, k)[0])
flow_path = []
flow_path.append(newsDate[0])
for i in range(0, sfc_len):
flow_path.append(
str(newsDate[2][2 * i]) + str(int(nf_number[i]) + 1))
flow_path.append(newsDate[1])
flow_path.append(flow_rate)
# print flow_path,flow_path[0],len(flow_path)
file.write(str(flow_path) + '\n')
for i in range(1, sfc_len + 1):
#print flow_path[len(flow_path)-1]
NF_load[flow_path[i]] = int(NF_load[flow_path[i]]) + int(
flow_path[len(flow_path) - 1])
file.closed
flow_vnf = file_path + '/alg1_NF_load.txt'
file = open(flow_vnf, 'w')
file.write(json.dumps(NF_load, indent=1))
file.closed
alg1_max_NF = 0
for i in NF_load:
if alg1_max_NF < NF_load[i]:
alg1_max_NF = NF_load[i]
fd = open(file_path + '/alg1_max_NF.txt', 'w')
fd.write(json.dumps(alg1_max_NF))
fd.closed
file = open(file_path + '/flow_feasible_vnf.txt', 'w')
for t in flowDic:
for n in range(0, 3):
for i in range(4, len(flowDic[t])):
flowDic[t][i] = random.randint(0, each_NF_num - 1)
line = str(flowDic[t])
newsDate = txt_wrap_by("'", "'", line, 0)
flow_rate = txt_wrap_by2(",", ",", line)[1]
#print "flow-rate",flow_rate
nf_number = [] #Save the serial number of each passed NF
h = txt_wrap_by2(",", ",", line)
for i in range(3, len(h)):
nf_number.append(h[i])
ff = find_n_sub_str(line, ",", 3, 0)
sfc_len = (len(newsDate[2]) + 1) / 2
k = find_n_sub_str(line, ",", 2 + sfc_len, 0)
nf_number.append(txt_wrap_by(",", "]", line, k)[0])
flow_path = []
flow_path.append(newsDate[0])
for i in range(0, sfc_len):
flow_path.append(
str(newsDate[2][2 * i]) + str(int(nf_number[i]) + 1))
flow_path.append(newsDate[1])
flow_path.append(flow_rate)
# print flow_path,flow_path[0],len(flow_path)
file.write(str(flow_path) + '\n')
file.closed
print "NFV Distribution Finished"
#coding=utf-8
from algorithms import dijkstra
from algorithms import dijkstra2
from algorithms import dijkstra3
from graph_for_l2 import DiGraph
from collections import defaultdict
import json
import os
CODEC = 'utf-8'
mynet = "rocketfuel_87s174h50nf.json"
g = DiGraph(mynet)
def txt_wrap_by(start_str, end_str, html,start):
keyvaule=[]
while start <=len(html):
start = html.find(start_str,start)
if start >= 0:
start += len(start_str)
end = html.find(end_str, start)
if end >= 0:
keyvaule.append(html[start:end].strip())
start = end + len(end_str)
else:
return keyvaule
def get_route_compare_algs(file_path):
all_node = []
all_node_alone = []
all_edge = []
all_edge_alone = []
all_edge_alone_order = []
def get_nfv_distribution(ratio, host_num, file_path):
CODEC = 'utf-8'
mynet = "rocketfuel_87s174h50nf.json"
g = DiGraph(mynet)
#Custom VNF processing power (1-10)
capacity = {
'F1': 10,
'F2': 10,
'F3': 10,
'F4': 10,
'F5': 10,
'F6': 10,
'F7': 10,
'F8': 10,
'F9': 10,
'F10': 10,
'I1': 10,
'I2': 10,
'I3': 10,
'I4': 10,
'I5': 10,
'I6': 10,
'I7': 10,
'I8': 10,
'I9': 10,
'I10': 10,
'P1': 10,
'P2': 10,
'P3': 10,
'P4': 10,
'P5': 10,
'P6': 10,
'P7': 10,
'P8': 10,
'P9': 10,
'P10': 10,
'D1': 10,
'D2': 10,
'D3': 10,
'D4': 10,
'D5': 10,
'D6': 10,
'D7': 10,
'D8': 10,
'D9': 10,
'D10': 10,
'W1': 10,
'W2': 10,
'W3': 10,
'W4': 10,
'W5': 10,
'W6': 10,
'W7': 10,
'W8': 10,
'W9': 10,
'W10': 10
}
each_NF_num = 10
#Enter two functional chains
#Number of streams between 80 hosts
flowDic = get_flows(host_num, ratio)
flow_number = len(flowDic)
print "flow_number", flow_number
#print flowDic
#Find out which streams of each type of NF have passed
flow = {}
flow['F'] = []
flow['I'] = []
flow['P'] = []
flow['D'] = []
flow['W'] = []
for key in flowDic:
if 'F' in str(flowDic[key][3]):
flow['F'].append(key)
if 'I' in str(flowDic[key][3]):
flow['I'].append(key)
if 'P' in str(flowDic[key][3]):
flow['P'].append(key)
if 'D' in str(flowDic[key][3]):
flow['D'].append(key)
if 'W' in str(flowDic[key][3]):
flow['W'].append(key)
#j stands for 9 processors, i stands for task (flow)
p = [([0] * len(flow) * 10) for i in range(len(flowDic))]
#print len(p),len(p[0])
for j in capacity.keys():
print j
#Calculate the processing power of Pij = stream bandwidth * distance to the NF (S-VNF-D) / NF
if 'F' in j:
#print "F",j
if '1' in j and '10' not in j:
row = 0
elif '2' in j:
row = 1
elif '3' in j:
row = 2
elif '4' in j:
row = 3
elif '5' in j:
row = 4
elif '6' in j:
row = 5
elif '7' in j:
row = 6
elif '8' in j:
row = 7
elif '9' in j:
row = 8
elif '10' in j:
#print "F10",j
row = 9
for i in flow['F']:
# print flowDic[i][0],j,flowDic[i][1]
path1 = dijkstra(g, flowDic[i][0], j)
path2 = dijkstra(g, j, flowDic[i][1])
distance = path1.get('cost') + path2.get('cost')
bandwidth = flowDic[int(i)][2]
power = capacity[j]
#print "power",power
#p[i-1][row] = bandwidth * distance / power
distance = math.sqrt(math.sqrt(distance))
p[i - 1][row] = bandwidth * distance / power
#p[i-1][row] = bandwidth
#print i
#print p[i-1][row]
elif 'I' in j:
if '1' in j and '10' not in j:
row = 10
elif '2' in j:
row = 11
elif '3' in j:
row = 12
elif '4' in j:
row = 13
elif '5' in j:
row = 14
elif '6' in j:
row = 15
elif '7' in j:
row = 16
elif '8' in j:
row = 17
elif '9' in j:
row = 18
elif '10' in j:
row = 19
for i in flow['I']:
path1 = dijkstra(g, flowDic[i][0], j)
path2 = dijkstra(g, j, flowDic[i][1])
distance = path1.get('cost') + path2.get('cost')
bandwidth = flowDic[int(i)][2]
power = capacity[j]
distance = math.sqrt(math.sqrt(distance))
p[i - 1][row] = bandwidth * distance / power
elif 'P' in j:
if '1' in j and '10' not in j:
row = 20
elif '2' in j:
row = 21
elif '3' in j:
row = 22
elif '4' in j:
row = 23
elif '5' in j:
row = 24
elif '6' in j:
row = 25
elif '7' in j:
row = 26
elif '8' in j:
row = 27
elif '9' in j:
row = 28
elif '10' in j:
row = 29
for i in flow['P']:
path1 = dijkstra(g, flowDic[i][0], j)
path2 = dijkstra(g, j, flowDic[i][1])
distance = path1.get('cost') + path2.get('cost')
bandwidth = flowDic[int(i)][2]
power = capacity[j]
distance = math.sqrt(math.sqrt(distance))
p[i - 1][row] = bandwidth * distance / power
elif 'D' in j:
if '1' in j and '10' not in j:
row = 30
elif '2' in j:
row = 31
elif '3' in j:
row = 32
elif '4' in j:
row = 33
elif '5' in j:
row = 34
elif '6' in j:
row = 35
elif '7' in j:
row = 36
elif '8' in j:
row = 37
elif '9' in j:
row = 38
elif '10' in j:
row = 39
for i in flow['D']:
path1 = dijkstra(g, flowDic[i][0], j)
path2 = dijkstra(g, j, flowDic[i][1])
distance = path1.get('cost') + path2.get('cost')
bandwidth = flowDic[int(i)][2]
power = capacity[j]
distance = math.sqrt(math.sqrt(distance))
p[i - 1][row] = bandwidth * distance / power
elif 'W' in j:
if '1' in j and '10' not in j:
row = 40
elif '2' in j:
row = 41
elif '3' in j:
row = 42
elif '4' in j:
row = 43
elif '5' in j:
row = 44
elif '6' in j:
row = 45
elif '7' in j:
row = 46
elif '8' in j:
row = 47
elif '9' in j:
row = 48
elif '10' in j:
row = 49
for i in flow['W']:
path1 = dijkstra(g, flowDic[i][0], j)
path2 = dijkstra(g, j, flowDic[i][1])
distance = path1.get('cost') + path2.get('cost')
bandwidth = flowDic[int(i)][2]
power = capacity[j]
distance = math.sqrt(math.sqrt(distance))
p[i - 1][row] = bandwidth * distance / power
'''
Solving linear equation
'''
#x = [[0 for col in range(len(flowDic))] for row in range(3)]
#x[i][j] ：Indicates that the ith stream passes through the jth vnf, and j(0-8) represents [F1, F2, F3, I1, I2, I3, P1, P2, P3]
'''Which F is passed through?'''
x = [[0 for col in range(10)] for row in range(len(flowDic))]
#print x
for i in range(0, len(flowDic)):
for j in range(0, 10):
x[i][j] = "x"
if len(flowDic) < 100000:
if i < 10:
x[i][j] = x[i][j] + "0000"
elif i < 100:
x[i][j] = x[i][j] + "000"
elif i < 1000:
x[i][j] = x[i][j] + "00"
elif i < 10000:
x[i][j] = x[i][j] + "0"
x[i][j] = x[i][j] + str(i) + str(j)
z = []
for i in range(0, len(flowDic)):
z.append("z" + str(i))
temp = []
for i in range(0, len(flowDic)):
for j in range(
0, 10): # 3 si the number of path that each flow can choose
temp.append(x[i][j])
for i in range(0, len(flowDic)):
temp.append(z[i])
prob = LpProblem('lptest', LpMinimize)
r = LpVariable('r', lowBound=0)
xx = LpVariable.dicts("", temp, lowBound=0,
upBound=1) #,cat = pulp.LpInteger
#print temp
print "-------2222222-----"
#print x[0]
#Add the target equation
#0-28 flows
prob += r
#0->F(0,1,2);1->I(3,4,5);2->P(6,7,8)
x_e = defaultdict(lambda: (defaultdict(lambda:
(defaultdict(lambda: None)))))
for i in range(10):
for j in range(len(flowDic)):
x_e[i][j][0] = x[j][i]
x_e[i][j][1] = p[j][i]
for i in range(0, 10):
prob += lpSum(xx[x_e[i][j][0]] * x_e[i][j][1] for j in x_e[i]) <= r
#Add constraints
for i in range(0, len(flowDic)):
prob += lpSum([xx[j] for j in x[i]]) == 1
GLPK().solve(prob)
print 'F_objective_sr =', value(prob.objective)
i = 0
j = 0
l = 0
for v in prob.variables():
#print v, v.varValue
l = l + 1
if l < flow_number * 10 + 1: #(the number of flows /cdot 3) +1
x[i][j] = v.varValue
if j < 9:
j = j + 1
else:
i = i + 1
j = 0
for i in range(0, flow_number):
k = 0
choose = 0
for j in range(0, 10):
if x[i][j] > k:
choose = j
k = x[i][j]
for j in range(0, 10):
if j == choose:
x[i][j] = 1
else:
x[i][j] = 0
for i in range(0, flow_number):
if ('F' in str(flowDic[i + 1][3])):
for j in range(0, 10):
if x[i][j] == 1:
flowDic[i + 1].append(j)
#print flowDic[i+1]
#sleep(600)
'''Which I passed through'''
#P_1 refers to the cost of I function
p_1 = [([0] * 10) for i in range(len(flowDic))]
#print "hh",len(p_1),len(p_1[0])
for i in range(len(flowDic)):
for j in range(10):
#print i,j,
p_1[i][j] = p[i][j + 10]
x1 = [[0 for col in range(10)] for row in range(len(flowDic))]
for i in range(0, len(flowDic)):
for j in range(0, 10):
x1[i][j] = "x"
if len(flowDic) < 100000:
if i < 10:
x1[i][j] = x1[i][j] + "0000"
elif i < 100:
x1[i][j] = x1[i][j] + "000"
elif i < 1000:
x1[i][j] = x1[i][j] + "00"
elif i < 10000:
x1[i][j] = x1[i][j] + "0"
x1[i][j] = x1[i][j] + str(i) + str(j)
z1 = []
for i in range(0, len(flowDic)):
z1.append("z" + str(i))
temp1 = []
for i in range(0, len(flowDic)):
for j in range(
0, 10): # 3 si the number of path that each flow can choose
temp1.append(x1[i][j])
for i in range(0, len(flowDic)):
temp1.append(z1[i])
prob1 = LpProblem('lptest1', LpMinimize)
r1 = LpVariable('r1', lowBound=0)
xx1 = LpVariable.dicts("", temp1, lowBound=0,
upBound=1) #, cat = pulp.LpInteger
#print xx1
prob1 += r1
#0->F(0,1,2);1->I(3,4,5);2->P(6,7,8)
x_e1 = defaultdict(lambda: (defaultdict(lambda:
(defaultdict(lambda: None)))))
for i in range(10):
for j in range(len(flowDic)):
x_e1[i][j][0] = x1[j][i]
x_e1[i][j][1] = p_1[j][i]
for i in range(0, 10):
prob1 += lpSum(xx1[x_e1[i][j][0]] * x_e1[i][j][1]
for j in x_e1[i]) <= r1
for i in range(0, len(flowDic)):
prob1 += lpSum([xx1[j] for j in x1[i]]) == 1
GLPK().solve(prob1)
print 'I_objective_sr =', value(prob1.objective)
i = 0
j = 0
l = 0
for v in prob1.variables():
l = l + 1
if l < flow_number * 10 + 1: #(the number of flows /cdot 3) +1
x[i][j] = v.varValue
if j < 9:
j = j + 1
else:
i = i + 1
j = 0
for i in range(0, flow_number):
k = 0
choose = 0
for j in range(0, 10):
if x[i][j] > k:
choose = j
k = x[i][j]
for j in range(0, 10):
if j == choose:
x[i][j] = 1
else:
x[i][j] = 0
for i in range(0, flow_number):
if ('I' in str(flowDic[i + 1][3])):
for j in range(0, 10):
if x[i][j] == 1:
flowDic[i + 1].append(j)
#print flowDic[i+1]
'''Which P passed?'''
p_3 = [([0] * 10) for i in range(len(flowDic))]
for i in range(len(flowDic)):
for j in range(10):
p_3[i][j] = p[i][j + 20]
x3 = [[0 for col in range(10)] for row in range(len(flowDic))]
for i in range(0, len(flowDic)):
for j in range(0, 10):
x3[i][j] = "x"
if len(flowDic) < 100000:
if i < 10:
x3[i][j] = x3[i][j] + "0000"
elif i < 100:
x3[i][j] = x3[i][j] + "000"
elif i < 1000:
x3[i][j] = x3[i][j] + "00"
elif i < 10000:
x3[i][j] = x3[i][j] + "0"
x3[i][j] = x3[i][j] + str(i) + str(j)
z3 = []
for i in range(0, len(flowDic)):
z3.append("z3" + str(i))
temp3 = []
for i in range(0, len(flowDic)):
for j in range(
0, 10): # 3 si the number of path that each flow can choose
temp3.append(x3[i][j])
for i in range(0, len(flowDic)):
temp3.append(z3[i])
prob3 = LpProblem('lptest3', LpMinimize)
r3 = LpVariable('r3', lowBound=0)
xx3 = LpVariable.dicts("", temp3, lowBound=0,
upBound=1) #, cat = pulp.LpInteger
x_e3 = defaultdict(lambda: (defaultdict(lambda:
(defaultdict(lambda: None)))))
for i in range(10):
for j in range(len(flowDic)):
x_e3[i][j][0] = x3[j][i]
x_e3[i][j][1] = p_3[j][i]
for i in range(0, 10):
prob3 += lpSum(xx3[x_e3[i][j][0]] * x_e3[i][j][1]
for j in x_e3[i]) <= r3
for i in range(0, len(flowDic)):
prob3 += lpSum([xx3[j] for j in x3[i]]) == 1
GLPK().solve(prob3)
print 'P_objective_sr =', value(prob3.objective)
i = 0
j = 0
l = 0
for v in prob3.variables():
l = l + 1
if l < flow_number * 10 + 1: #(the number of flows /cdot 3) +1
x[i][j] = v.varValue
if j < 9:
j = j + 1
else:
i = i + 1
j = 0
for i in range(0, flow_number):
k = 0
choose = 0
for j in range(0, 10):
if x[i][j] > k:
choose = j
k = x[i][j]
for j in range(0, 10):
if j == choose:
x[i][j] = 1
else:
x[i][j] = 0
for i in range(0, flow_number):
if ('P' in str(flowDic[i + 1][3])):
for j in range(0, 10):
if x[i][j] == 1:
flowDic[i + 1].append(j)
#print flowDic[i+1]
'''Which D is passed through?'''
p_4 = [([0] * 10) for i in range(len(flowDic))]
for i in range(len(flowDic)):
for j in range(10):
p_4[i][j] = p[i][j + 30]
x4 = [[0 for col in range(10)] for row in range(len(flowDic))]
for i in range(0, len(flowDic)):
for j in range(0, 10):
x4[i][j] = "x"
if len(flowDic) < 100000:
if i < 10:
x4[i][j] = x4[i][j] + "0000"
elif i < 100:
x4[i][j] = x4[i][j] + "000"
elif i < 1000:
x4[i][j] = x4[i][j] + "00"
elif i < 10000:
x4[i][j] = x4[i][j] + "0"
x4[i][j] = x4[i][j] + str(i) + str(j)
z4 = []
for i in range(0, len(flowDic)):
z4.append("z4" + str(i))
temp4 = []
for i in range(0, len(flowDic)):
for j in range(
0, 10): # 3 si the number of path that each flow can choose
temp4.append(x4[i][j])
for i in range(0, len(flowDic)):
temp4.append(z4[i])
prob4 = LpProblem('lptest4', LpMinimize)
r4 = LpVariable('r4', lowBound=0)
xx4 = LpVariable.dicts("", temp4, lowBound=0,
upBound=1) #, cat = pulp.LpInteger
prob4 += r4
x_e4 = defaultdict(lambda: (defaultdict(lambda:
(defaultdict(lambda: None)))))
for i in range(10):
for j in range(len(flowDic)):
x_e4[i][j][0] = x4[j][i]
x_e4[i][j][1] = p_4[j][i]
for i in range(0, 10):
prob4 += lpSum(xx4[x_e4[i][j][0]] * x_e4[i][j][1]
for j in x_e4[i]) <= r4
for i in range(0, len(flowDic)):
prob4 += lpSum([xx4[j] for j in x4[i]]) == 1
GLPK().solve(prob4)
print 'D_objective_sr =', value(prob4.objective)
i = 0
j = 0
l = 0
for v in prob4.variables():
l = l + 1
if l < flow_number * 10 + 1: #(the number of flows /cdot 3) +1
x[i][j] = v.varValue
if j < 9:
j = j + 1
else:
i = i + 1
j = 0
for i in range(0, flow_number):
k = 0
choose = 0
for j in range(0, 10):
if x[i][j] > k:
choose = j
k = x[i][j]
for j in range(0, 10):
if j == choose:
x[i][j] = 1
else:
x[i][j] = 0
for i in range(0, flow_number):
if ('D' in str(flowDic[i + 1][3])):
for j in range(0, 10):
if x[i][j] == 1:
flowDic[i + 1].append(j)
#print flowDic[i+1]
'''Which W to solve'''
p_5 = [([0] * 10) for i in range(len(flowDic))]
for i in range(len(flowDic)):
for j in range(10):
p_5[i][j] = p[i][j + 40]
x5 = [[0 for col in range(10)] for row in range(len(flowDic))]
for i in range(0, len(flowDic)):
for j in range(0, 10):
x5[i][j] = "x"
if len(flowDic) < 100000:
if i < 10:
x5[i][j] = x5[i][j] + "0000"
elif i < 100:
x5[i][j] = x5[i][j] + "000"
elif i < 1000:
x5[i][j] = x5[i][j] + "00"
elif i < 10000:
x5[i][j] = x5[i][j] + "0"
x5[i][j] = x5[i][j] + str(i) + str(j)
z5 = []
for i in range(0, len(flowDic)):
z5.append("z5" + str(i))
temp5 = []
for i in range(0, len(flowDic)):
for j in range(
0, 10): # 3 si the number of path that each flow can choose
temp5.append(x5[i][j])
for i in range(0, len(flowDic)):
temp5.append(z5[i])
prob5 = LpProblem('lptest5', LpMinimize)
r5 = LpVariable('r5', lowBound=0)
xx5 = LpVariable.dicts("", temp5, lowBound=0,
upBound=1) #, cat = pulp.LpInteger
#print xx3
prob5 += r5
x_e5 = defaultdict(lambda: (defaultdict(lambda:
(defaultdict(lambda: None)))))
for i in range(10):
for j in range(len(flowDic)):
x_e5[i][j][0] = x5[j][i]
x_e5[i][j][1] = p_5[j][i]
for i in range(0, 10):
prob5 += lpSum(xx5[x_e5[i][j][0]] * x_e5[i][j][1]
for j in x_e5[i]) <= r5
for i in range(0, len(flowDic)):
prob5 += lpSum([xx5[j] for j in x5[i]]) == 1
GLPK().solve(prob5)
print 'W_objective_sr =', value(prob5.objective)
i = 0
j = 0
l = 0
for v in prob5.variables():
l = l + 1
if l < flow_number * 10 + 1: #(the number of flows /cdot 3) +1
x[i][j] = v.varValue
if j < 9:
j = j + 1
else:
i = i + 1
j = 0
for i in range(0, flow_number):
k = 0
choose = 0
for j in range(0, 10):
if x[i][j] > k:
choose = j
k = x[i][j]
for j in range(0, 10):
if j == choose:
x[i][j] = 1
else:
x[i][j] = 0
for i in range(0, flow_number):
if ('W' in str(flowDic[i + 1][3])):
for j in range(0, 10):
if x[i][j] == 1:
flowDic[i + 1].append(j)
#print flowDic[i+1]
flow_vnf = file_path + '/flow_vnf.txt'
file = open(flow_vnf, 'w')
NF_load = (defaultdict(lambda: None))
for i in capacity:
NF_load[i] = 0
for t in flowDic:
line = str(flowDic[t])
newsDate = txt_wrap_by("'", "'", line, 0)
flow_rate = txt_wrap_by2(",", ",", line)[1]
#print "flow-rate",flow_rate
nf_number = [] #Save the serial number of each passed NF
h = txt_wrap_by2(",", ",", line)
for i in range(3, len(h)):
nf_number.append(h[i])
ff = find_n_sub_str(line, ",", 3, 0)
sfc_len = (len(newsDate[2]) + 1) / 2
k = find_n_sub_str(line, ",", 2 + sfc_len, 0)
#print "2222222222",line,k, txt_wrap_by(",","]",line,k)
nf_number.append(txt_wrap_by(",", "]", line, k)[0])
flow_path = []
flow_path.append(newsDate[0])
for i in range(0, sfc_len):
flow_path.append(
str(newsDate[2][2 * i]) + str(int(nf_number[i]) + 1))
flow_path.append(newsDate[1])
flow_path.append(flow_rate)
# print flow_path,flow_path[0],len(flow_path)
file.write(str(flow_path) + '\n')
for i in range(1, sfc_len + 1):
#print flow_path[len(flow_path)-1]
NF_load[flow_path[i]] = int(NF_load[flow_path[i]]) + int(
flow_path[len(flow_path) - 1])
file.closed
flow_vnf = file_path + '/alg1_NF_load.txt'
file = open(flow_vnf, 'w')
file.write(json.dumps(NF_load, indent=1))
file.closed
alg1_max_NF = 0
for i in NF_load:
if alg1_max_NF < NF_load[i]:
alg1_max_NF = NF_load[i]
fd = open(file_path + '/alg1_max_NF.txt', 'w')
fd.write(json.dumps(alg1_max_NF))
fd.closed
file = open(file_path + '/flow_feasible_vnf.txt', 'w')
for t in flowDic:
for n in range(0, 3):
for i in range(4, len(flowDic[t])):
flowDic[t][i] = random.randint(0, each_NF_num - 1)
line = str(flowDic[t])
newsDate = txt_wrap_by("'", "'", line, 0)
flow_rate = txt_wrap_by2(",", ",", line)[1]
#print "flow-rate",flow_rate
nf_number = [] #Save the serial number of each passed NF
h = txt_wrap_by2(",", ",", line)
for i in range(3, len(h)):
nf_number.append(h[i])
ff = find_n_sub_str(line, ",", 3, 0)
sfc_len = (len(newsDate[2]) + 1) / 2
k = find_n_sub_str(line, ",", 2 + sfc_len, 0)
nf_number.append(txt_wrap_by(",", "]", line, k)[0])
flow_path = []
flow_path.append(newsDate[0])
for i in range(0, sfc_len):
flow_path.append(
str(newsDate[2][2 * i]) + str(int(nf_number[i]) + 1))
flow_path.append(newsDate[1])
flow_path.append(flow_rate)
# print flow_path,flow_path[0],len(flow_path)
file.write(str(flow_path) + '\n')
file.closed
print "NFV Distribution Finished"