A Best Practice Guide to Resource Forecasting for Computing Systems

Recently, measurement-based studies of software systems have proliferated, reflecting an increasingly empirical focus on system availability, reliability, aging, and fault tolerance. However, it is a nontrivial, error-prone, arduous, and time-consuming task even for experienced system administrators...

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Bibliographic Details
Published in:IEEE transactions on reliability 2007-12, Vol.56 (4), p.615-628
Main Authors: Hoffmann, G.A., Trivedi, K.S., Malek, M.
Format: Article
Language:English
Subjects:
Aging
Apache web server
Availability
Best practices
Computer programs
Electric communication systems
Empirical analysis
Failure analysis
failure forecasting
Fault tolerant systems
Forecasting
Mathematical analysis
Mathematical models
monitoring
non-parametric modeling
Performance analysis
prediction of resource utilization
Predictive models
quantitative analysis
Sensitivity analysis
Servers
Software
Software measurement
Software systems
statistical modeling
Studies
telecommunication systems
Web server
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Summary:Recently, measurement-based studies of software systems have proliferated, reflecting an increasingly empirical focus on system availability, reliability, aging, and fault tolerance. However, it is a nontrivial, error-prone, arduous, and time-consuming task even for experienced system administrators, and statistical analysts to know what a reasonable set of steps should include to model, and successfully predict performance variables, or system failures of a complex software system. Reported results are fragmented, and focus on applying statistical regression techniques to monitored numerical system data. In this paper, we propose a best practice guide for building empirical models based on our experience with forecasting Apache web server performance variables, and forecasting call availability of a real-world telecommunication system. To substantiate the presented guide, and to demonstrate our approach in a step by step manner, we model, and predict the response time, and the amount of free physical memory of an Apache web server system, as well as the call availability of an industrial telecommunication system. Additionally, we present concrete results for a) variable selection where we cross benchmark three procedures, b) empirical model building where we cross benchmark four techniques, and c) sensitivity analysis. This best practice guide intends to assist in configuring modeling approaches systematically for best estimation, and prediction results.
ISSN:0018-9529
1558-1721
DOI:10.1109/TR.2007.909764