Issue
DARTS, Volume 4, Issue 1
Special Issue of the 13th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2018)
-
Part of:
Volume:
DARTS, Volume 4 (ECOOP 2018)
Journal: Dagstuhl Artifacts Series (DARTS)
Publication Details
- published at: 2018-05-23
- Publisher: Schloss Dagstuhl – Leibniz-Zentrum für Informatik
- DBLP: db/journals/darts/darts4
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Document
Front Matter - SEAMS 2018 Artifacts, Table of Contents, Preface, Artifact Evaluation Committee
Abstract
Front Matter - SEAMS 2018 Artifacts, Table of Contents, Preface, Artifact Evaluation Committee
Cite as
Special Issue of the 13th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2018). Dagstuhl Artifacts Series (DARTS), Volume 4, Issue 1, pp. 0:i-0:xiii, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
Copy BibTex To Clipboard
@Article{bures_et_al:DARTS.4.1.0,
author = {Bures, Tomas and Weyns, Danny and Andersson, Jesper},
title = {{ Front Matter - SEAMS 2018 Artifacts, Table of Contents, Preface, Artifact Evaluation Committee}},
pages = {0:i--0:xiii},
journal = {Dagstuhl Artifacts Series},
ISSN = {2509-8195},
year = {2018},
volume = {4},
number = {1},
editor = {Bures, Tomas and Weyns, Danny and Andersson, Jesper},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/DARTS.4.1.0},
URN = {urn:nbn:de:0030-drops-87096},
doi = {10.4230/DARTS.4.1.0},
annote = {Keywords: Front Matter - SEAMS 2018 Artifacts, Table of Contents, Preface, Artifact Evaluation Committee}
}
Document
mRUBiS: An Exemplar for Model-Based Architectural Self-Healing and Self-Optimization (Artifact)
Abstract
Self-adaptive software systems are often structured into an adaptation engine that manages an adaptable software by operating on a runtime model that represents the architecture of the software (model-based architectural self-adaptation). Despite the popularity of such approaches, existing exemplars provide application programming interfaces but no runtime model to develop adaptation engines. Consequently, there does not exist any exemplar that supports developing, evaluating, and comparing model-based self-adaptation off the shelf. Therefore, we present mRUBiS, an extensible exemplar for model-based architectural self-healing and self-optimization. mRUBiS simulates the adaptable software and therefore provides and maintains an architectural runtime model of the software, which can be directly used by adaptation engines to realize and perform self-adaptation. Particularly, mRUBiS supports injecting issues into the model, which should be handled by self-adaptation, and validating the model to assess the self-adaptation. For this purpose, the exemplar provides two case studies of self-healing and self-optimization. Finally, mRUBiS allows developers to explore variants of adaptation engines (e.g., event-driven self-adaptation) and to evaluate the effectiveness, efficiency, and scalability of the engines.
Cite as
Thomas Vogel. mRUBiS: An Exemplar for Model-Based Architectural Self-Healing and Self-Optimization (Artifact). In Special Issue of the 13th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2018). Dagstuhl Artifacts Series (DARTS), Volume 4, Issue 1, pp. 1:1-1:4, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@Article{vogel:DARTS.4.1.1,
author = {Vogel, Thomas},
title = {{mRUBiS: An Exemplar for Model-Based Architectural Self-Healing and Self-Optimization (Artifact)}},
pages = {1:1--1:4},
journal = {Dagstuhl Artifacts Series},
ISSN = {2509-8195},
year = {2018},
volume = {4},
number = {1},
editor = {Vogel, Thomas},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/DARTS.4.1.1},
URN = {urn:nbn:de:0030-drops-87102},
doi = {10.4230/DARTS.4.1.1},
annote = {Keywords: Self-adaptation, architecture, runtime models, simulator}
}
Document
K8-Scalar: a workbench to compare autoscalers for container-orchestrated services (Artifact)
Abstract
This artifact is an easy-to-use and extensible workbench exemplar, named K8-Scalar, which allows researchers to implement and evaluate different self-adaptive approaches to autoscaling container-orchestrated services. The workbench is based on Docker, a popular technology for easing the deployment of containerized software that also has been positioned as an enabler for reproducible research. The workbench also relies on a container orchestration framework: Kubernetes (K8s), the de-facto industry standard for orchestration and monitoring of elastically scalable container-based services. Finally, it integrates and extends Scalar, a generic testbed for evaluating the scalability of large-scale systems with support for evaluating the performance of autoscalers for database clusters.
The associated scholarly paper presents (i) the architecture and implementation of K8-Scalar and how a particular autoscaler can be plugged in, (ii) sketches the design of a Riemann-based autoscaler for database clusters, (iii) illustrates how to design, setup and analyze a series of experiments to configure and evaluate the performance of this autoscaler for a particular database (i.e., Cassandra) and a particular workload type, (iv) and validates the effectiveness of K8-scalar as a workbench for accurately comparing the performance of different auto-scaling strategies. Future work includes extending K8-Scalar with an improved research data management repository.
Cite as
Wito Delnat, Thomas Heyman, Wouter Joosen, Davy Preuveneers, Ansar Rafique, Eddy Truyen, and Dimitri Van Landuyt. K8-Scalar: a workbench to compare autoscalers for container-orchestrated services (Artifact). In Special Issue of the 13th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2018). Dagstuhl Artifacts Series (DARTS), Volume 4, Issue 1, pp. 2:1-2:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
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@Article{delnat_et_al:DARTS.4.1.2,
author = {Delnat, Wito and Heyman, Thomas and Joosen, Wouter and Preuveneers, Davy and Rafique, Ansar and Truyen, Eddy and Van Landuyt, Dimitri},
title = {{K8-Scalar: a workbench to compare autoscalers for container-orchestrated services (Artifact)}},
pages = {2:1--2:6},
journal = {Dagstuhl Artifacts Series},
ISSN = {2509-8195},
year = {2018},
volume = {4},
number = {1},
editor = {Delnat, Wito and Heyman, Thomas and Joosen, Wouter and Preuveneers, Davy and Rafique, Ansar and Truyen, Eddy and Van Landuyt, Dimitri},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/DARTS.4.1.2},
URN = {urn:nbn:de:0030-drops-87118},
doi = {10.4230/DARTS.4.1.2},
annote = {Keywords: Container orchestration, autoscalers, experimentation exemplar}
}