Title :
A Forecasting Capability Study of Empirical Mode Decomposition for the Arrival Time of a Parallel Batch System
Author :
Ngo, Linh ; Apon, Amy ; Hoffman, Doug
Author_Institution :
Comput. Sci. & Comput. Eng., Univ. of Arkansas, Fayetteville, AR, USA
Abstract :
This paper demonstrates the feasibility and potential of applying empirical mode decomposition (EMD) to forecast the arrival time behaviors in a parallel batch system. An analysis of the workload records shows the existence of daily and weekly patterns within the workload. Results show that the intrinsic mode functions (IMF), products of the sifting/decomposition process of EMD, produce a better prediction than the original arrival histogram when used in a simple weight-matching prediction technique. Promising applications include the implementation of an EMD/neural network combination.
Keywords :
batch processing (computers); neural nets; parallel processing; arrival time behaviors; decomposition process; empirical mode decomposition; forecasting capability study; intrinsic mode functions; neural network; parallel batch system; sifting process; weight-matching prediction technique; Automatic testing; Electronic mail; Error correction; IP networks; Information filtering; Information filters; Internet; Phase detection; Protection; Telecommunication traffic; Empirical Mode Decomposition; forecasting; neural network; time series; workload;
Conference_Titel :
Information Technology: New Generations (ITNG), 2010 Seventh International Conference on
Conference_Location :
Las Vegas, NV
Print_ISBN :
978-1-4244-6270-4
DOI :
10.1109/ITNG.2010.138
