def predict_vm(ecs_infor_array, input_file_array):
#Get the CPU information
CPU_kernel, CPU_memory, N_Pvm, condition, Pvm, Predict_time, Predict_Start = utils.splitEscData(
ecs_infor_array)
#Get the History Data information
length, Hvm, History_Start = utils.splitInputData(input_file_array)
#History Data
#Statistic and Split
#lenD,S_Data=utils.Statistic_Split(length,Hvm,N_Pvm,Pvm)
lenD, S_Data = utils.Denoise_Split(length, Hvm, N_Pvm, Pvm)
#print S_Data
result = []
if ecs_infor_array is None:
print 'ecs information is none'
return result
if input_file_array is None:
print 'input file information is none'
return result
#-----------------------Mirror-------------------------
#NEPvm=mirror.Mirror(lenD,N_Pvm,S_Data,Predict_time)
#-----------------------Smirror-------------------------
#NEPvm=mirror.Smirror(lenD,N_Pvm,S_Data,Predict_time)
#-----------------------Smirror-------------------------
NEPvm = mirror.Commirror(lenD, N_Pvm, S_Data, Predict_time)
# allocation
CPU, N_PCPU = Box.Boxing(NEPvm, Pvm, N_Pvm, CPU_kernel, CPU_memory,
condition)
print N_PCPU
result = utils.results_expression(CPU, N_PCPU, N_Pvm, Pvm)
return result
def predict_vm(ecs_infor_array, input_file_array):
#Get the CPU information
CPU_kernel, CPU_memory, N_Pvm, condition, Pvm, Predict_time, Predict_Start = utils.splitEscData(
ecs_infor_array)
#Get the History Data information
length, Hvm, History_Start = utils.splitInputData(input_file_array)
#History Data
lenD, S_Data = utils.Denoise_Split(length, Hvm, N_Pvm, Pvm)
#print S_Data
result = []
if ecs_infor_array is None:
print 'ecs information is none'
return result
if input_file_array is None:
print 'input file information is none'
return result
#--------------------method one estimate--------------
NEPvm = TDEstimation.EstTD(History_Start, Predict_Start, lenD, N_Pvm,
S_Data, Predict_time)
print NEPvm
# allocation
CPU, N_PCPU = Box.Boxing(NEPvm, Pvm, N_Pvm, CPU_kernel, CPU_memory,
condition)
print N_PCPU
result = utils.results_expression(CPU, N_PCPU, N_Pvm, Pvm)
return result
def predict_vm(ecs_infor_array,input_file_array):
#Get the CPU information
N_Stype,Servers,N_Pvm,Pvm,Predict_time,Predict_Start=utils.splitEscData(ecs_infor_array)
#Get the History Data information
length,Hvm,History_End=utils.splitInputData(input_file_array)
#History Data
Hdate=datetime.datetime.strptime(History_End,"%Y-%m-%d %H:%M:%S").date()
#Statistic and Split
#lenD,S_Data=utils.Statistic_Split(length,Hvm,N_Pvm,Pvm)
lenD,S_Data=utils.Denoise_Split(length,Hvm,N_Pvm,Pvm)
# deal with gaps
gaps=int(round((utils.getTimeDiff(Predict_Start,History_End))/86400))
for i in range(N_Pvm):
for j in range(gaps):
S_Data[i].append(S_Data[i][(-7)])
result = []
if ecs_infor_array is None:
print 'ecs information is none'
return result
if input_file_array is None:
print 'input file information is none'
return result
if(N_Pvm>5):
return
V=3.3
NEPvm=mirror.Commirror(lenD,N_Pvm,S_Data,Predict_time,V)
for i in range(N_Pvm):
if((Pvm[i][0]=="flavor3")and(Hdate.month>6)):
NEPvm[i]=int(NEPvm[i]*19)
else:
#add value
#V=4
V=0
NEPvm=mirror.Smirror(lenD,N_Pvm,S_Data,Predict_time,V)
for i in range(N_Pvm):
if(Pvm[i][0]=="flavor8"):
NEPvm[i]=int(NEPvm[i]*1.2)
# allocation
Servers_N,P_Servers=Allocation.Allocate(NEPvm,Pvm,N_Stype,Servers)
result=utils.results_expression(P_Servers,Servers_N,Servers,Pvm)
return result
def predict_vm(ecs_infor_array,input_file_array):
#Get the CPU information
N_Stype,Servers,N_Pvm,Pvm,Predict_time,Predict_Start=utils.splitEscData(ecs_infor_array)
#Get the History Data information
length,Hvm,History_End=utils.splitInputData(input_file_array)
#History Data
#Statistic and Split
#lenD,S_Data=utils.Statistic_Split(length,Hvm,N_Pvm,Pvm)
lenD,S_Data=utils.Denoise_Split(length,Hvm,N_Pvm,Pvm)
# deal with gaps
gaps=int(round((utils.getTimeDiff(Predict_Start,History_End))/86400))
for i in range(N_Pvm):
for j in range(gaps):
S_Data[i].append(S_Data[i][-7])
print S_Data
result = []
if ecs_infor_array is None:
print 'ecs information is none'
return result
if input_file_array is None:
print 'input file information is none'
return result
#-----------------------Smirror-------------------------
#NEPvm=mirror.Smirror(lenD,N_Pvm,S_Data,Predict_time)
#-----------------------Smirror-------------------------
#NEPvm=mirror.Commirror(lenD,N_Pvm,S_Data,Predict_time)
#------------------------ES-----------------------------
NEPvm=ES.CES(lenD,N_Pvm,S_Data,Predict_time)
print NEPvm
# allocation
Servers_N,P_Servers=Allocation.Allocate(NEPvm,Pvm,N_Stype,Servers)
S=Score.Score(NEPvm,Pvm,Servers_N,P_Servers,Servers)
print S
result=utils.results_expression(P_Servers,Servers_N,Servers,Pvm)
return result
