A moving average method for predicting process resource usage based on a state transition model

Author

Moriguchi, Shuischi ; Munctomo, M. ; Sato, Yoshiharu

Author_Institution

Graduate Sch. of Eng., Hokkaido Univ. Sapporo, Japan

fYear

1998

fDate

20-21 Aug 1998

Firstpage

82

Lastpage

85

Abstract

We develop a prediction algorithm for process resource usage based on a state transition model. The state transition model is built by using a k-means clustering algorithm applied to a series of 2-dimensional observed parameters on process resource usage such as load average and free memory in a computer. Our prediction algorithm estimates the parameters from state transition probabilities of the model. To reduce prediction error, we introduce a moving average method in the prediction algorithm

Keywords

distributed processing; moving average processes; parameter estimation; probability; resource allocation; 2D observed parameters; free memory; k-means clustering algorithm; load average; moving average method; parameter estimation; prediction error; process resource usage prediction; state transition model; state transition probabilities; Accuracy; Clustering algorithms; Distributed computing; Electronic mail; Equations; Petroleum; Prediction algorithms; Predictive models; Probability;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Information Processing Society - NAFIPS, 1998 Conference of the North American

Conference_Location

Pensacola Beach, FL

Print_ISBN

0-7803-4453-7

Type

conf

DOI

10.1109/NAFIPS.1998.715540

Filename

715540