SimuLizar

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Palladio Addon (Liste)
Name SimuLizar
Contacts Matthias Becker (http://www.hni.uni-paderborn.de/swt/mitarbeiter/132887696303222/)
State Stable
Is Stand-alone Analysis? Yes
Extends Analyses
Extends Metamodels
Code Location https://github.com/PalladioSimulator/Palladio-Analyzer-SimuLizar
Update Site https://sdqweb.ipd.kit.edu/eclipse/simulizar/nightly/

Short Summary

SimuLizar is a Palladio plug-in for analyzing self-adaptive systems, such as cloud computing systems, at design-time. With SimuLizar, we want to provide modeling support for self-adaptation rules as well as new analysis for scalability, elasticity, and efficiency.

Documentation

What is SimuLizar?

SimuLizarLogo.png

SimuLizar is a Palladio plug-in for analyzing self-adaptive systems, such as cloud computing systems, at design-time. With SimuLizar, we want to provide modeling support for self-adaptation rules as well as new analysis for scalability, elasticity, and efficiency.

Install SimuLizar

(This documentation is for users who want to just use SimuLizar)


  1. Download the latest Eclipse Modelling Tools edition and install Palladio via the all-in-one Palladio update site found under Palladio nightly update site or Palladio latest stable release. Alternatively you can start with the Palladio all-in-one drop.
  2. Install SimuLizar via the same update site you used to install Palladio

Alternatively, you can use Eclipse Installer to Set up a Palladio Development Environment

Setup SimuLizar Development Workspace

(This documentation is for developing with SimuLizar)

  1. Download latest Eclipse Modelling Tools. Try using the latest service release.
  2. Clone the desired projects from https://github.com/PalladioSimulator/ at least https://github.com/PalladioSimulator/Palladio-Analyzer-SimuLizar
  3. Either clone from their respective repositories or install Palladio Core, Editors, SimuCom and QuAL (except deprecated components) via the update site: https://updatesite.palladio-simulator.com/palladio-build-updatesite/nightly/.

Alternatively, you can use Eclipse Installer in Advanced Mode to Set up a Palladio Development Environment and clone the desired projects (at least Palladio-Analyzer-SimuLizar)

Further documents

  1. See this tutorial for an example to get started with SimuLizar Simulizar Tutorial
  2. See the QuAL documentation for the measurments, metrics, and storage backend notes
  3. Cloud Metrics you can analyze with SimuLizar

Getting Started

SimuLizar Example Cloud Computing System

A simple self-adaptive system model which can be analyzed with SimuLizar can be obtained from our GitHub repository [1]. This system consists a load balancer and two cloud computing servers running. Each cloud computing server is running an application instance. However, initially only one server is active, i.e., the load balancer directs the whole workload to this server. Only in case the overall response time exceeds the threshold of 3 seconds, the second server will be activated and load is delegated to it. This is done in 10% steps until the load balancer equally directs 50% of the load to each server.

[1] https://github.com/PalladioSimulator/Palladio-Analyzer-SimuLizar/tree/master/bundles/ExampleModels/org.palladiosimulator.simulizar.examples.loadbalancer

Transient Effects and Reconfiguration Costs

The execution of reconfigurations can result in an additional overhead, which can deteriorate the quality of the system. Additionally, the execution duration may depend on the current utilization of the system: If, e.g., a VM is migrated in a highly utilized subnet, the migration takes longer than when it is migrated in a fairly utilized subnet. SimuLizar supports the consideration of these types of interdependencies between reconfiguration duration, reconfiguration cost and system performance. We refer to these interdependencies as transient effects.

SimuLizar supports the analysis of transient effects via the fully integrated Adaptation Action metamodel and analysis extension. We outline the core functionality on a separate page.

Publications

  • Matthias Becker, Markus Luckey, and Steffen Becker: Performance analysis of self-adaptive systems for requirements validation at design-time. In Proceedings of the 9th international ACM Sigsoft conference on Quality of software architectures (QoSA '13), p. 43-52. ACM, New York, NY, USA, 2013. ACM Digital Library link.
  • Matthias Becker, Joachim Meyer, and Steffen Becker: SimuLizar: Design-Time Modeling and Performance Analysis of Self-Adaptive Systems. In Proceedings of the Software Engineering Conference (SE 2013). Aachen, 2013.

Contact

SimuLizar is developed at the University of Paderborn as part of the two research projects SFB901 and CloudScale. In case you have questions about SimuLizar, please contact Matthias Becker.