def Boxing(NEPvm,Pvm,N_Pvm,CPU_kernal,CPU_memory):
VMs=[]
# all Predicted vms
for i in range(N_Pvm):
for j in range(int(NEPvm[i])):
VMs.append(Pvm[i])
lenVMs=len(VMs) # The number of all predicted VMs
# Split vms according to M/K
VM1=[];
VM2=[];
VM4=[];
for i in range(lenVMs):
VMs_info=[VMs[i][1],VMs[i][2]]
if (VMs_info[1]/VMs_info[0]==1):
VM1.append(VMs[i])
elif(VMs_info[1]/VMs_info[0]==2):
VM2.append(VMs[i])
else:
VM4.append(VMs[i])
Min=min([len(VM1),len(VM2),len(VM4)])
# maybe zero
if (Min==0):
Min=1
if(len(VM4)==0):
P4=1
Min=min([len(VM1),len(VM2)])
P2=int(math.ceil(len(VM2)/Min))
P1=int(math.ceil(len(VM1)/Min))
elif(len(V2)==0):
P2=1
Min=min([len(VM1),len(VM4)])
P4=int(math.ceil(len(VM4)/Min))
P1=int(math.ceil(len(VM1)/Min))
else:
P1=1
Min=min([len(VM2),len(VM4)])
P2=int(math.ceil(len(VM2)/Min))
P4=int(math.ceil(len(VM4)/Min))
else:
P4=int(math.ceil(len(VM4)/Min))
P2=int(math.ceil(len(VM2)/Min))
P1=int(math.ceil(len(VM1)/Min))
idx4=Cond_Sort(VM4)
idx2=Cond_Sort(VM2)
idx1=Cond_Sort(VM1)
VMs=[] #reset
i4=0
i2=0
i1=0
for i in range(Min):
for j in range(i4,(i4+P4),1):
if(j<len(VM4)):
VMs.append(VM4[idx4[j]])
i4=i4+1
for z in range(i2,(i2+P2),1):
if(z<len(VM2)):
VMs.append(VM2[idx2[z]])
i2=i2+1
for t in range(i1,(i1+P1),1):
if(t<len(VM1)):
VMs.append(VM1[idx1[t]])
i1=i1+1
CPU=[]
CPU.append([])
N_PCPU=0 #default 0
VMSC=copy.deepcopy(VMs)
while(1):
CPU_limit=[CPU_kernal,CPU_memory]
lenVM=len(VMs)
for j in range(lenVM):
VMs_info=[VMs[j][1],VMs[j][2]]
if(CPU_limit[0]>=VMs_info[0] and CPU_limit[1]>=VMs_info[1]):
CPU[N_PCPU].append(VMs[j][0])
CPU_limit[0]=CPU_limit[0]-VMs_info[0]
CPU_limit[1]=CPU_limit[1]-VMs_info[1]
VMSC.remove(VMs[j])
if(utils.SUM_Judge(VMSC,CPU_kernal,CPU_memory)):
#CPU[0]=CLRes(CPU[0],VMSC,Pvm,N_Pvm,CPU_kernal,CPU_memory)
break
else:
VMs=copy.deepcopy(VMSC)
CPU.append([])
N_PCPU=N_PCPU+1
return CPU,(N_PCPU+1)
def Boxing(NEPvm, Pvm, N_Pvm, CPU_kernel, CPU_memory, condition):
VMs = []
# all Predicted vms
for i in range(N_Pvm):
for j in range(int(NEPvm[i])):
VMs.append(Pvm[i])
VMs = First_Delete(VMs, CPU_kernel, CPU_memory, condition)
lenVMs = len(VMs) # The number of all predicted VMs
# Split vms according to M/K
VM1 = []
VM2 = []
VM4 = []
for i in range(lenVMs):
VMs_info = [VMs[i][1], VMs[i][2]]
if (VMs_info[1] / VMs_info[0] == 1):
VM1.append(VMs[i])
elif (VMs_info[1] / VMs_info[0] == 2):
VM2.append(VMs[i])
else:
VM4.append(VMs[i])
VMs = [] #reset
VM4 = Adjust(VM4, 0)
VM2 = Adjust(VM2, 0)
VM1 = Adjust(VM1, 0)
T_VMs = [VM4, VM2, VM1]
len4 = len(VM4)
len2 = len(VM2)
len1 = len(VM1)
#maybe exist zero
if (len4 == 0):
len4 = 100
if (len2 == 0):
len2 = 100
if (len1 == 0):
len1 = 100
for i in range(lenVMs):
TEMP = [(len(T_VMs[0]) / len4), (len(T_VMs[1]) / len2),
(len(T_VMs[2]) / len1)]
M = TEMP.index(max(TEMP))
if (len(T_VMs[M]) != 0):
VMs.append(T_VMs[M][0])
(T_VMs[M]).remove(T_VMs[M][0])
CPU = []
CPU.append([])
CPULR = [] #resorce left
N_PCPU = 0 #default 0
VMSC = copy.deepcopy(VMs)
while (1):
CPU_limit = [CPU_kernel, CPU_memory]
lenVM = len(VMs)
for j in range(lenVM):
VMs_info = [VMs[j][1], VMs[j][2]]
if (CPU_limit[0] >= VMs_info[0] and CPU_limit[1] >= VMs_info[1]):
CPU[N_PCPU].append(VMs[j][0])
CPU_limit[0] = CPU_limit[0] - VMs_info[0]
CPU_limit[1] = CPU_limit[1] - VMs_info[1]
VMSC.remove(VMs[j])
CPULR.append(CPU_limit)
if (utils.SUM_Judge(VMSC, CPU_kernel, CPU_memory)):
CPU = Optimize(CPU, CPULR, VMSC, Pvm, N_Pvm)
break
else:
VMs = copy.deepcopy(VMSC)
CPU.append([])
N_PCPU = N_PCPU + 1
return CPU, (N_PCPU + 1)