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A synthetic workload generation technique for stress testing session-based systems

delete2006-11-01
delete68
PRE
AI
D
Diwakar Krishnamurthy *
J
Jerome Rolia
S
Shikharesh Majumdar
DOI:10.1109/TSE.2006.106delete
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Abstract

Abstract

En 中文
Enterprise applications are often business critical but lack effective synthetic workload generation techniques to evaluate performance. These workloads are characterized by sessions of interdependent requests that often cause and exploit dynamically generated responses. Interrequest dependencies must be reflected in synthetic workloads for these systems to exercise application functions correctly. This poses significant challenges for automating the construction of representative synthetic workloads and manipulating workload characteristics for sensitivity analyses. This paper presents a technique to overcome these problems. Given request logs for a system under study, the technique automatically creates a synthetic workload that has specified characteristics and maintains the correct interrequest dependencies. The technique is demonstrated through a case study involving a TPC-W e-commerce system. Results show that incorrect performance results can be obtained by neglecting interrequest dependencies, thereby highlighting the value of our technique. The study also exploits our technique to investigate the impact of several workload characteristics on system performance. Results establish that high variability in the distributions of session length, session idle times, and request service times can cause increased contention among sessions, leading to poor system responsiveness. To the best of our knowledge, these are the first results of this kind for a session-based system. We believe our technique is of value for studies where fine control over workload is essential.
Keywords:
performance of systems
measurement techniques
modeling techniques
software engineering
testing tools
Internet applications
electronic commerce
Web servers
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Journal

IEEE Transactions on Software Engineering cover
IEEE Transactions on Software Engineering
IF:
5.6
Papers:
2.8K
Citations:
1.1W

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