Short-term performance management by priority-based queueing

Christian Markl; Oliver Hühn; Martin Bichler

doi:10.1007/s11761-010-0066-3

Short-term performance management by priority-based queueing

Christian Markl, Oliver Hühn, Martin Bichler

Informatics 18 - Chair of Decision Sciences und Systems

Technical University of Munich

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

Service-based IT infrastructures serve many different business processes on a shared infrastructure in parallel. The automated request execution on the interconnected software components, hosted on heterogeneous hardware resources, is typically orchestrated by distributed transaction processing (DTP) systems. While pre-defined quality-of-service metrics must be met, IT providers have to deal with short-term demand fluctuations. Adaptive prioritization is a way to react to short-term demand variances. Performance modeling can be applied to predict the impact of prioritization on the overall performance of the system. In this paper, we describe the workload characteristics and particularities of two real-world DTP systems and evaluate the effects of prioritization regarding overall load and end-to-end performance measures.

Original language	English
Pages (from-to)	169-180
Number of pages	12
Journal	Service Oriented Computing and Applications
Volume	4
Issue number	3
DOIs	https://doi.org/10.1007/s11761-010-0066-3
State	Published - 2010

Keywords

Capacity management
IT service management
Performance modeling
Prioritization
Transaction processing

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10.1007/s11761-010-0066-3

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title = "Short-term performance management by priority-based queueing",

abstract = "Service-based IT infrastructures serve many different business processes on a shared infrastructure in parallel. The automated request execution on the interconnected software components, hosted on heterogeneous hardware resources, is typically orchestrated by distributed transaction processing (DTP) systems. While pre-defined quality-of-service metrics must be met, IT providers have to deal with short-term demand fluctuations. Adaptive prioritization is a way to react to short-term demand variances. Performance modeling can be applied to predict the impact of prioritization on the overall performance of the system. In this paper, we describe the workload characteristics and particularities of two real-world DTP systems and evaluate the effects of prioritization regarding overall load and end-to-end performance measures.",

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author = "Christian Markl and Oliver H{\"u}hn and Martin Bichler",

note = "Funding Information: Acknowledgments The project was funded by means of the German Federal Ministry of Economy and Technology under the promotional reference “01MQ07012”. The authors take the responsibility for the contents.",

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AU - Markl, Christian

AU - Hühn, Oliver

AU - Bichler, Martin

N1 - Funding Information: Acknowledgments The project was funded by means of the German Federal Ministry of Economy and Technology under the promotional reference “01MQ07012”. The authors take the responsibility for the contents.

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N2 - Service-based IT infrastructures serve many different business processes on a shared infrastructure in parallel. The automated request execution on the interconnected software components, hosted on heterogeneous hardware resources, is typically orchestrated by distributed transaction processing (DTP) systems. While pre-defined quality-of-service metrics must be met, IT providers have to deal with short-term demand fluctuations. Adaptive prioritization is a way to react to short-term demand variances. Performance modeling can be applied to predict the impact of prioritization on the overall performance of the system. In this paper, we describe the workload characteristics and particularities of two real-world DTP systems and evaluate the effects of prioritization regarding overall load and end-to-end performance measures.

AB - Service-based IT infrastructures serve many different business processes on a shared infrastructure in parallel. The automated request execution on the interconnected software components, hosted on heterogeneous hardware resources, is typically orchestrated by distributed transaction processing (DTP) systems. While pre-defined quality-of-service metrics must be met, IT providers have to deal with short-term demand fluctuations. Adaptive prioritization is a way to react to short-term demand variances. Performance modeling can be applied to predict the impact of prioritization on the overall performance of the system. In this paper, we describe the workload characteristics and particularities of two real-world DTP systems and evaluate the effects of prioritization regarding overall load and end-to-end performance measures.

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KW - IT service management

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KW - Transaction processing

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Short-term performance management by priority-based queueing

Abstract

Keywords

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