WESSBAS: extraction of probabilistic workload specifications for load testing and performance prediction—a model-driven approach for session-based application systems
WESSBAS: extraction of probabilistic workload specifications for load testing and performance prediction—a model-driven approach for session-based application systems
The specification of workloads is required in order to evaluate performance characteristics of application systems using load testing and model-based performance prediction. Defining workload specifications that represent the real workload as accurately as possible is one of the biggest challenges in both areas. To overcome this challenge, this paper presents an approach that aims to automate the extraction and transformation of workload specifications for load testing and model-based performance prediction of session-based application systems. The approach (WESSBAS) comprises three main components. First, a system- and tool-agnostic domain-specific language (DSL) allows the layered modeling of workload specifications of session-based systems. Second, instances of this DSL are automatically extracted from recorded session logs of production systems. Third, these instances are transformed into executable workload specifications of load generation tools and model-based performance evaluation tools. We present transformations to the common load testing tool Apache JMeter and to the Palladio Component Model. Our approach is evaluated using the industry-standard benchmark SPECjEnterprise2010 and the World Cup 1998 access logs. Workload-specific characteristics (e.g., session lengths and arrival rates) and performance characteristics (e.g., response times and CPU utilizations) show that the extracted workloads match the measured workloads with high accuracy.
Load testing, Performance models, Performance prediction, Workload specifications
443-477
Vögele, Christian
8e1c8c3c-9e2a-44a7-ad3f-923c829680cf
van Hoorn, André
eb23729b-7858-44ae-8c0a-d9e940de7b99
Schulz, Eike
cfa22481-3b22-407a-b335-42efcc41e157
Hasselbring, Wilhelm
ee89c5c9-a900-40b1-82c1-552268cd01bd
Krcmar, Helmut
573ec0c1-5734-4324-a833-e99c231e9f96
May 2018
Vögele, Christian
8e1c8c3c-9e2a-44a7-ad3f-923c829680cf
van Hoorn, André
eb23729b-7858-44ae-8c0a-d9e940de7b99
Schulz, Eike
cfa22481-3b22-407a-b335-42efcc41e157
Hasselbring, Wilhelm
ee89c5c9-a900-40b1-82c1-552268cd01bd
Krcmar, Helmut
573ec0c1-5734-4324-a833-e99c231e9f96
Vögele, Christian, van Hoorn, André, Schulz, Eike, Hasselbring, Wilhelm and Krcmar, Helmut
(2018)
WESSBAS: extraction of probabilistic workload specifications for load testing and performance prediction—a model-driven approach for session-based application systems.
Software and Systems Modeling, 17 (2), .
(doi:10.1007/s10270-016-0566-5).
Abstract
The specification of workloads is required in order to evaluate performance characteristics of application systems using load testing and model-based performance prediction. Defining workload specifications that represent the real workload as accurately as possible is one of the biggest challenges in both areas. To overcome this challenge, this paper presents an approach that aims to automate the extraction and transformation of workload specifications for load testing and model-based performance prediction of session-based application systems. The approach (WESSBAS) comprises three main components. First, a system- and tool-agnostic domain-specific language (DSL) allows the layered modeling of workload specifications of session-based systems. Second, instances of this DSL are automatically extracted from recorded session logs of production systems. Third, these instances are transformed into executable workload specifications of load generation tools and model-based performance evaluation tools. We present transformations to the common load testing tool Apache JMeter and to the Palladio Component Model. Our approach is evaluated using the industry-standard benchmark SPECjEnterprise2010 and the World Cup 1998 access logs. Workload-specific characteristics (e.g., session lengths and arrival rates) and performance characteristics (e.g., response times and CPU utilizations) show that the extracted workloads match the measured workloads with high accuracy.
Text
s10270-016-0566-5
- Version of Record
More information
Accepted/In Press date: 4 October 2016
e-pub ahead of print date: 20 October 2016
Published date: May 2018
Keywords:
Load testing, Performance models, Performance prediction, Workload specifications
Identifiers
Local EPrints ID: 488712
URI: http://eprints.soton.ac.uk/id/eprint/488712
ISSN: 1619-1366
PURE UUID: d2adcb4f-e892-4e71-a9ff-9bd2c199f3d1
Catalogue record
Date deposited: 04 Apr 2024 16:48
Last modified: 10 Apr 2024 02:15
Export record
Altmetrics
Contributors
Author:
Christian Vögele
Author:
André van Hoorn
Author:
Eike Schulz
Author:
Wilhelm Hasselbring
Author:
Helmut Krcmar
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics