Institut für Organisation und Management von Informationssystemen

Unser Institut beschäftigt sich mit Fragestellungen, wie autonomem Management von Informationsstrukturen, effizienter Realisierung von Cloud- oder Clustersystemen und wie dabei eine Kooperation von Anwendung, Middleware und Hardwaremanagement bei der Bereitstellung der Dienste erreicht werden kann.

Für weitere Informationen besuchen Sie unsere Seite zu den Forschungsschwerpunkten und den laufenden Projekten.

 

Unsere letzten Publikationen


Seybold, Daniel; Keppler, Moritz; Gründler, Daniel; Domaschka, Jörg
Mowgli: Finding YourWay in the DBMS Jungle
International Conference on Performance Engineering (ICPE),
April 2019
akzeptiert
Schanzel, Benjamin; Leznik, Mark; Volpert, Simon; Domaschka, Jörg; Wesner, Stefan
Unified Container Environments for Scientific Cluster Scenarios
In Janczyk, Michael; Suchodoletz, Dirk von; Wiebelt, Bernd;, Editor, Proceedings of the 5th bwHPC Symposium
April 2019

Zusammenfassung: Providing runtime dependencies for computational workflows in shared environments, like HPC clusters, requires appropriate management efforts from users and administrators. Users of a cluster define the software stack required for a workflow to execute successfully, while administrators maintain the mechanisms to offer libraries and applications in different versions and combinations for the users to have maximum flexibility. The Environment Modules system is the tool of choice on bwForCluster BinAC for this purpose. In this paper, we present a solution to execute a workflow which relies on a software stack not available via Environment Modules on BinAC. The paper describes the usage of a containerized, user-defined software stack for this particular problem using the Singularity and Docker container platforms. Additionally, we present a solution for the reproducible provisioning of identical software stacks across HPC and non-HPC environments. The approach uses a Docker image as the basis for a Singularity container. This allows users to define arbitrary software stacks giving them the ability to execute their workflows across different environments, from local workstations to HPC clusters. This approach provides identical versions of software and libraries across all environments.

Sarker, Mitalee; Wesner, Stefan
Statistical Model Based Cloud Resource Management
Economics of Grids, Clouds, Systems, and Services. GECON 2018 , Seite 107-115.
Februar 2019
ISBN: 978-3-030-13341-2
Mazumdar, Somnath; Seybold, Daniel; Kritikos, Kyriakos; Verginadis, Yiannis
A Survey on Data Storage and PlacementMethodologies for Cloud-Big Data Ecosystem
Journal of Big Data,
2019
akzeptiert
Baur, Daniel; Griesinger, Frank; Verginadis, Yiannis; Stefanidis, Vasilis; Patiniotakis, Ioannis
A Model Driven Engineering Approach for Flexible and Distributed Monitoring of Cross-Cloud Applications
11th IEEE/ACM International Conference on Utility and Cloud Computing
Dezember 2018
akzeptiert
Baur, Daniel
A provider agnostic approach to multi-cloud orchestration
ACM/IFIP International Middleware Conference Doctoral Symposium
Dezember 2018
akzeptiert

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