CPU Load Prediction Model for Distributed Computing

Resources performance forecasting constitutes one of particularly significant research problems in distributed computing. To ensure an adequate use of the computing resources in a metacomputing environment, there is a need for effective and flexible forecasting method to determine the available perf...

Full description

Saved in:
Bibliographic Details
Main Authors: Bey, K.B., Benhammadi, F., Mokhtari, A., Guessoum, Z.
Format: Conference Proceeding
Language:English
Subjects:
Condition monitoring
CPU load prediction
Distributed computing
Grid computing
Informatics
Laboratories
Load forecasting
Load modeling
Metacomputing
Military computing
neuro-fuzzy system
performance modeling
Predictive models
Resources monitoring
task scheduling
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Resources performance forecasting constitutes one of particularly significant research problems in distributed computing. To ensure an adequate use of the computing resources in a metacomputing environment, there is a need for effective and flexible forecasting method to determine the available performance on each resource. In this paper, we present a modeling approach to estimating the future value of CPU load. This modeling prediction approach uses the combination of adaptive network-based fuzzy inference systems (ANFIS) and the clustering process applied on the CPU Load time series. Experiments show the feasibility and effectiveness of this approach that achieves significant improvement and outperforms the existing CPU load prediction models reported in literature.
ISSN:2379-5352
DOI:10.1109/ISPDC.2009.8