NDLI: An Investigation into the Application of Different Performance Prediction Methods to Distributed Enterprise Applications

Content Provider	Springer Nature Link
Author	Bacigalupo, David A. Jarvis, Stephen A. He, Ligang Spooner, Daniel P. Dillenberger, Donna N. Nudd, Graham R.
Copyright Year	2005
Abstract	Response time predictions for workload on new server architectures can enhance Service Level Agreement–based resource management. This paper evaluates two performance prediction methods using a distributed enterprise application benchmark. The historical method makes predictions by extrapolating from previously gathered performance data, while the layered queuing method makes predictions by solving layered queuing networks. The methods are evaluated in terms of: the systems that can be modelled; the metrics that can be predicted; the ease with which the models can be created and the level of expertise required; the overheads of recalibrating a model; and the delay when evaluating a prediction. The paper also investigates how a prediction-enhanced resource management algorithm can be tuned so as to compensate for predictive inaccuracy and balance the costs of SLA violations and server usage.
Starting Page	93
Ending Page	111
Page Count	19
File Format	PDF
ISSN	09208542
Journal	The Journal of Supercomputing
Volume Number	34
Issue Number	2
e-ISSN	15730484
Language	English
Publisher	Kluwer Academic Publishers
Publisher Date	2005-01-01
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	performance prediction distributed enterprise application layered queuing modelling historical performance data resource management service level agreement Computer Science Processor Architectures Programming Languages, Compilers, Interpreters
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Information Systems Hardware and Architecture Software

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