Performance Evaluation and Prediction for Legacy Information Systems

Database-centric information systems are critical to the operations of large organisations. In particular, they often process a large amount of data with stringent performance requirements. Currently, however, there is a lack of systematic approaches to evaluating and predicting their performance wh...

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Bibliographic Details
Published in:29th International Conference on Software Engineering (ICSE'07) pp. 540 - 549
Main Authors: Yan Jin, Tang, A., Jun Han, Yan Liu
Format: Conference Proceeding
Language:English
Published: IEEE 01.05.2007
Subjects:
Australia
Capacity planning
Hardware
Information systems
Performance analysis
Predictive models
Production systems
Software performance
System performance
ISBN:9780769528281, 0769528287
ISSN:0270-5257
Online Access:Get full text
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Summary:Database-centric information systems are critical to the operations of large organisations. In particular, they often process a large amount of data with stringent performance requirements. Currently, however, there is a lack of systematic approaches to evaluating and predicting their performance when they are subject to an exorbitant growth of workload. In this paper, we introduce such a systematic approach that combines benchmarking, production system monitoring, and performance modelling (BMM) to address this issue. The approach helps the performance analyst to understand the system's operating environment and quantify its performance characteristics under varying load conditions via monitoring and benchmarking. Based on such realistic measurements, modelling techniques are used to predict the system performance. Our experience of applying BMM to a real-world system demonstrates the capability of BMM in predicting the performance of existing and enhanced software architectures in planning for its capacity growth.
Bibliography:SourceType-Conference Papers & Proceedings-1
ObjectType-Conference Paper-1
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ISBN:9780769528281
0769528287
ISSN:0270-5257
DOI:10.1109/ICSE.2007.64