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The Descartes Modeling Language

The Descartes Modeling Language (DML) is a new architecture-level modeling language for modeling Quality-of-Service and resource management related aspects of modern dynamic IT systems, infrastructures and services. DML is designed to serve as a basis for self-aware resource management during operation ensuring that system QoS requirements are continuously satisfied while infrastructure resources are utilized as efficiently as possible. The term Quality-of-Service (QoS) is used to refer to non-functional system properties including performance (considering classical metrics such as response time, throughput, scalability and efficiency) and dependability (considering availability, reliability and security aspects).

The current version of DML is focused on performance including capacity, responsiveness and resource efficiency aspects, however, work is underway to provide support for modeling further QoS properties. The modeling language itself is designed in a generic fashion and is intended to eventually support the full spectrum of QoS properties mentioned above.

DML has a modular structure and is provided as a set of meta-models for:

  • Resource Landscape
  • Application Architecture
  • Adaptation Points
  • Adaptation Process.

These sub-meta-models can be used both in offline and online settings for application scenarios like system sizing, capacity planning and trade-off analysis. In an online setting, DML provides the basis for self-aware resource management during operation.

The DML core aspects and key features are:

  • Reflecting different levels of service behavior abstraction
  • Probabilistic modeling of dependencies between model parameters
  • Detailed modeling of the resource landscape including layers like virtualization and middleware
  • Description of dynamic aspects to define the system configuration space
  • Adaptation language to model system adaptation processes
  • End-2-end modeling approach for adaptive systems
  • Implemented in 

The Descartes Modeling Language is specified in the following technical report that will be published soon. You can already download the preliminary version.

  • S. Kounev, F. Brosig, and N. Huber. Descartes Meta-Model (DMM). Technical report, Karlsruhe Institute of Technology (KIT), 2014. [ bib ]

The EMF projects containing the respective meta-models specified in Ecore can be obtained as zip-archive.


Recent presentations given at the RELATE ITN Open Excellence Workshop about the vision of the Descartes Research Group and the realization of the Descartes Meta-Model are:

  • Samuel Kounev. Design-Time vs. Run-Time Models for Quality-of-Service Prediction. 2012. [ slides ]
  • Fabian Brosig. New Concepts for Online Architecture-Level Performance Models. 2012. [ slides ]
  • Nikolaus Huber. Model-based Run-Time Adaptation in Dynamic Virtualized Resource Landscapes. 2012. [ slides ]

Most recent publications

  1. Fabian Brosig, Nikolaus Huber, and Samuel Kounev. Architecture-Level Software Performance Abstractions for Online Performance Prediction. Elsevier Science of Computer Programming Journal (SciCo), 2013. [ bib | DOI | http | .pdf ]
  2. Nikolaus Huber, André van Hoorn, Anne Koziolek, Fabian Brosig, and Samuel Kounev. Modeling Run-Time Adaptation at the System Architecture Level in Dynamic Service-Oriented Environments. Service Oriented Computing and Applications, 2013, Springer-Verlag. [ bib | .pdf ]
  3. Nikolaus Huber, André van Hoorn, Anne Koziolek, Fabian Brosig, and Samuel Kounev. S/T/A: Meta-Modeling Run-Time Adaptation in Component-Based System Architectures. In 9th IEEE International Conference on e-Business Engineering (ICEBE 2012), Hangzhou, China, September 9-11 2012. Acceptance Rate (Full Paper): 19.7% (26/132). [ bibhttp.pdf ]
  4. Fabian Brosig, Nikolaus Huber, and Samuel Kounev. Modeling Parameter and Context Dependencies in Online Architecture-Level Performance Models. In Proceedings of the 15th ACM SIGSOFT International Symposium on Component Based Software Engineering (CBSE 2012), June 26-28 2012. Acceptance Rate (Full Paper): 28.5%. [ bib | .pdf ]
  5. Nikolaus Huber, Fabian Brosig, and Samuel Kounev. Modeling Dynamic Virtualized Resource Landscapes. In Proceedings of the 8th ACM SIGSOFT International Conference on the Quality of Software Architectures (QoSA 2012), Bertinoro, Italy, June 25-28 2012. Acceptance Rate (Full Paper): 25.6%. [ bib| .pdf ]