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
