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计算网络拓扑所需要的各种函数集合.py
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计算网络拓扑所需要的各种函数集合.py
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import numpy as np
import mini.Dijistla as sp
import math
class method_all():
def __init__(self,nodenum = 11):
self.initmap = np.zeros((nodenum,nodenum))
self.Loadij = [0.11, 0.11, 0.1, 0.12, 0.17, 0.2, 0.17,
0.16, 0.14, 0.25, 0.25, 0.24, 0.3, 0.22]
# self.Delayij = [48, 25, 32, 15, 17, 38, 47, 22, 5, 37,
# 50, 26, 47, 45]
self.Delayij = [0.1937993680714527, 0.2540040648119312, 0.1271125502714918, 0.18183462269821038,
0.4206863293186338, 0.3380733504775385, 0.3228030858947195, 0.377369398579886,
0.2261626365440943, 0.34807538535028737,
0.572568032597279, 0.2978922416173892, 0.15322597466080183, 0.3129914666351893]
self.Cij = [460,470,490,380,450,350,450,550,280,430,440,360,450,450]
self.maxbw=[500,560,800,660,900,700,800,750,600,800,800,800,800,900]
self.nodes = []
if nodenum == 11:
self.nodes=[[1,2],[1,3],[1,4],[1,5],[2,6],[2,7],[3,6],[4,9],[5,9],[6,8],[7,10],
[8,9],[8,10],[9,10]]
elif nodenum == 10:
self.nodes = [[0, 1], [0, 2], [0, 3], [0, 4], [1, 5], [1, 6], [2, 5], [3, 8], [4, 8], [5, 7], [6, 9],
[7, 8], [7, 9], [8, 9]]
self.D0 = max(self.Delayij)
self.lastvi = 0
# self.initmap = self.fuzhi(self.initmap,self.Cij,self.Delayij,self.Loadij,a,b,c)
# print(self.initmap)
def fuzhi(self, map, cij, delay, load, a, b, c):
i = 0
_ = float('inf')
for j in self.nodes:
self.writedata(map, j[0], j[1], cij[i], delay[i], load[i], cij, delay, load, a, b, c)
self.writedata(map, j[1], j[0], cij[i], delay[i], load[i], cij, delay, load, a, b, c)
i += 1
for i in range(len(map)):
for j in range(len(map)):
if map[i][j] == 0:
map[i][j] = _
return map
def writedata(self, map, i, j, bw, de, diu, cij, Delayij, Loadij, a, b, c):
map[i][j] = self.quanzhi(bw, de, diu, cij, Delayij, Loadij, a, b, c)
def getabc(self, a=0.1, b=0.3, c=0.6):
return a, b, c
def quanzhi(self, bw, de, diu, cij, Delayij, Loadij, a, b, c):
Cri = bw / self.average(cij)
Dri = de / self.average(Delayij)
Lri = diu / self.average(Loadij)
# 自设权重指标
# lpri=(a*Lri+b*Dri)/(c*Cri);
return (a * Lri + b * Dri) / (c * Cri)
def average(self, k):
return sum(k) / len(k)
def getshorstpath(self,path,map,threat,uui):
allpath={}
num = 0
while len(path)>1:
# print("最短路径：", self.path)
allpath.setdefault(num,[])
allpath[num] = path
# print(self.allpath)
self.dellink2(num,path,map,threat,uui)
path, map = sp.Dijistla(map,1,10).map()
print(path)
num+=1
return allpath
#更改map
def dellink(self,path,map):
_ = float("inf")
k = len(path)
# print(k)
for i in range(k):
if i+1==k:
break
map[path[i]][path[i+1]] = _
map[path[i+1]][path[i]] = _
return map
#更改map和权值
def dellink2(self,num,path,map,threat,uui):
_ = float("inf")
k = len(path)
Upi = 1000
uui.setdefault(num,[])
# print(k)
for i in range(k):
if i+1==k:
break
try:
k1 = self.nodes.index([path[i],path[i+1]])
except:
k1 = self.nodes.index([path[i+1],path[i]])
# 计算UPi即最大的利用率
bwmax = (self.maxbw[k1]- self.Cij[k1])/self.maxbw[k1]*2*self.D0/self.Delayij[k1]
temp = (self.maxbw[k1]- self.Cij[k1])/self.maxbw[k1]
uui[num].append((temp,k1))
if bwmax<Upi:
Upi = bwmax
map[path[i]][path[i+1]] = _
threat.append(Upi)
def getrate(self,list,allrate):
all = 0
for i in list:
all+=i
k = len(list)
for i in range(k):
allrate.append(list[i]/all)
def wanshanUpi(self, path, list):
k = len(path)
for i in range(k):
self.kk(path[i], list)
def kk(self, path, list):
k = len(path)
for i in range(k):
if i + 1 == k:
break
try:
list.append([path[i], path[i + 1]])
except:
list.append([path[i + 1], path[i]])
def updaremap(self,map,cij,delay,load,a,b,c):
i = 0
_ = float('inf')
nodes = self.nodes
cij = self.Cij
delay = self.Delayij
load = self.Loadij
for j in nodes:
self.writedata(map,j[0], j[1],cij[i],delay[i],load[i],cij,delay,load,a,b,c)
self.writedata(map,j[1], j[0],cij[i],delay[i],load[i],cij,delay,load,a,b,c)
i += 1
for i in range(len(map)):
for j in range(len(map)):
if map[i][j] == 0:
map[i][j] = _
return map
def result(self,path,threat,list):
# list = [50, 100, 150, 200, 250,300,350,400,450,500]
# vi =0
k = len(path)
resultlist = []
while True:
for i in range(k):
vi = self.returnresult(list,threat[i],path[i],i)
print(vi)
resultlist.append(vi)
m=0
flag = []
for j in resultlist:
if j == -1 :
print("第"+str(m)+"条路径时延太大")
m += 1
continue
if j == -2 :
print("第"+str(m)+"条路径带宽不够")
m += 1
continue
if j == 0:
m += 1
continue
flag.append(1)
if len(flag) == k:
return resultlist
def returnresult(self,list,threat,path,k):
vi = 100
num = 0
while True:
# print(str(threat) + " , " + str(vi))
if math.fabs(threat - vi) < 0.09:
if vi > threat:
return self.lastvi
print(str(threat)+" , "+str(vi))
return vi
if num > len(list)-1:
num=0
value = list[num]
vi = self.getMaxVi(value,path,k,threat)
if vi == self.lastvi and self.isoutbw == 1:
self.isoutbw = 0
return vi
#是否超过了threat
if self.isoutthreat == 1:
self.isoutthreat=0
return vi
if vi == -1:
print("延时太大")
elif vi == -2:
print("带宽不够")
return vi
num+=1
def getMaxVi(self,b2,path,a,threat,cij,delay,uui):
k = len(path)
Vi = 0
for i in range(k):
if i+1==k:
break
try:
k1 = self.nodes.index([path[i], path[i + 1]])
except:
k1 = self.nodes.index([path[i+1], path[i]])
#计算Vi
b1 = self.maxbw[k1] - cij[k1]
# print("k1 "+str(k1)+" b1 "+str(b1)+" b2 "+ str(b2) +" "+str(sets.setting().maxbw[k1]))
vi = b1/self.maxbw[k1]
#区最大的vi
if vi>Vi:
if vi > threat :
self.isoutthreat = 1
continue
Vi = vi
k = len(uui[a])
# print(k)
Utlist = []
Ut=0
# 判断条件 总延时小于 Dci
for i in range(k):
try:
k1 = self.nodes.index([path[i], path[i + 1]])
Ut = delay[k1]/(1-uui[a][i][0])
if Ut > (self.D0 * 2):
return -1
# print(self.uui[a][i][1])
delay[uui[a][i][1]] = Ut
# 判断条件 剩余带宽大于要分配的带宽
if cij[uui[a][i][1]]>b2:
self.lastvi = Vi
cij[uui[a][i][1]]-=b2
else:
self.isoutbw = 1
return self.lastvi
except:
pass
return Vi
def updatepath(self,bw,path,rate,list,cij,delay):
paths = path
m = len(paths)
for j in range(m):
if j+1==m:
break
try:
k1 = self.nodes.index([paths[j],paths[j+1]])
except:
k1 = self.nodes.index([paths[j+1],paths[j]])
self.Cij[k1]= self.Cij[k1]-bw*rate
tempdelay = (self.maxbw[k1] - cij[k1]) / self.maxbw[k1]
Ut = delay[k1] / (1 - tempdelay)
list.append(tempdelay)
delay[k1] = Ut