Institute of Information Resource Management

We currently focus our activities on autonomous Management of Information infrastructures, efficient realisation of Cloud- and Clustersystems and how through tight integration of application, middleware and hardware management service provision can be optimized.

Further information can be found on our research and project pages.


Our latest publications

Seybold, Daniel; Keppler, Moritz; Gründler, Daniel; Domaschka, Jörg
Mowgli: Finding YourWay in the DBMS Jungle
International Conference on Performance Engineering (ICPE),
April 2019
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

Abstract: 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 , page 107-115.
February 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,
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
December 2018
Baur, Daniel
A provider agnostic approach to multi-cloud orchestration
ACM/IFIP International Middleware Conference Doctoral Symposium
December 2018
Seybold, Daniel; Hauser, Christopher B.; Eisenhart, Georg; Volpert, Simon; Domaschka, Jörg
The Impact of the Storage Tier: A Baseline Performance Analysis of containerized DBMS
Workshop on Container-based Systems for Big Data, Distributed and Parallel computing @ Euro-Par 2018,
October 2018
Hauser, Christopher B.; Wesner, Stefan
Reviewing Cloud Monitoring: Towards Cloud Resource Profiling
IEEE 11th International Conference on Cloud Computing (IEEE CLOUD 2018)
July 2018
Hauser, Christopher B.; Domaschka, Jörg; Wesner, Stefan
Predictability of Resource Intensive Big Data and HPC Jobs in Cloud Data Centres
IEEE International Workshop on System Reliability in Cloud Computing and Big Data
July 2018
Leznik, Mark; Volpert, Simon; Griesinger, Frank; Seybold, Daniel; Domaschka, Jörg
Done Yet? A Critical Introspective of the Cloud Management Toolbox
24th IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC),
June 2018
ISBN: 978-1-5386-1468-6

Click here to get an overview of all publications.