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