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Modeling and Extracting Load Intensity Profiles

Modeling and Extracting Load Intensity Profiles Modeling and Extracting Load Intensity Profiles ´ JOAKIM VON KISTOWSKI, NIKOLAS HERBST and SAMUEL KOUNEV, ¨ University of WURZBURG HENNING GROENDA and CHRISTIAN STIER, FZI Forschungszentrum Informatik, Karlsruhe SEBASTIAN LEHRIG, s-lab ­ Software Quality Lab, Paderborn University Today's system developers and operators face the challenge of creating software systems that make efficient use of dynamically allocated resources under highly variable and dynamic load profiles, while at the same time delivering reliable performance. Autonomic controllers, for example, an advanced autoscaling mechanism in a cloud computing context, can benefit from an abstracted load model as knowledge to reconfigure on time and precisely. Existing workload characterization approaches have limited support to capture variations in the interarrival times of incoming work units over time (i.e., a variable load profile). For example, industrial and scientific benchmarks support constant or stepwise increasing load, or interarrival times defined by statistical distributions or recorded traces. These options show shortcomings either in representative character of load variation patterns or in abstraction and flexibility of their format. In this article, we present the Descartes Load Intensity Model (DLIM) approach addressing these issues. DLIM provides a modeling formalism for describing load intensity variations over time. A DLIM instance is http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Autonomous and Adaptive Systems (TAAS) Association for Computing Machinery

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References (17)

Publisher
Association for Computing Machinery
Copyright
Copyright © 2017 by ACM Inc.
ISSN
1556-4665
DOI
10.1145/3019596
Publisher site
See Article on Publisher Site

Abstract

Modeling and Extracting Load Intensity Profiles ´ JOAKIM VON KISTOWSKI, NIKOLAS HERBST and SAMUEL KOUNEV, ¨ University of WURZBURG HENNING GROENDA and CHRISTIAN STIER, FZI Forschungszentrum Informatik, Karlsruhe SEBASTIAN LEHRIG, s-lab ­ Software Quality Lab, Paderborn University Today's system developers and operators face the challenge of creating software systems that make efficient use of dynamically allocated resources under highly variable and dynamic load profiles, while at the same time delivering reliable performance. Autonomic controllers, for example, an advanced autoscaling mechanism in a cloud computing context, can benefit from an abstracted load model as knowledge to reconfigure on time and precisely. Existing workload characterization approaches have limited support to capture variations in the interarrival times of incoming work units over time (i.e., a variable load profile). For example, industrial and scientific benchmarks support constant or stepwise increasing load, or interarrival times defined by statistical distributions or recorded traces. These options show shortcomings either in representative character of load variation patterns or in abstraction and flexibility of their format. In this article, we present the Descartes Load Intensity Model (DLIM) approach addressing these issues. DLIM provides a modeling formalism for describing load intensity variations over time. A DLIM instance is

Journal

ACM Transactions on Autonomous and Adaptive Systems (TAAS)Association for Computing Machinery

Published: Jan 10, 2017

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