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

Hauser, Christopher B.
Self-organized and Flexible Distributed Resource Cluster: ‘DisResc’
In 2nd Cloud Forward, Editor,
Oktober 2016

Zusammenfassung: The idea of DisResc is to place workloads with different requirements on heterogeneous resources, while both the requirements and the resources are considered. The overall goals are to better utilise (heterogeneous) data centres, provide better user experiences by selecting the best matching hardware for a workload, and to allow different workload types like virtual machines, containers or HPC jobs side by side in one data centre. DisResc is the vision to build a cluster management software for cloud and hpc workloads, running in parallel on a heterogeneous physical data centre. DisResc enabled compute nodes should i) run virtual machines, containers or HPC jobs, ii) compile time-based behaviour profiles of their workloads, in order to iii) detect suboptimal situations like over/under utilization. The resource utilisation should consider multiple metrics like processor, memory, disk, and network utilisation. The cluster should communicate in a peer-based manner to agree on the best fitting placement of new workloads, and workloads of nodes in a suboptimal state. This non-centralised approach can remove single points for management and monitoring, which are usually found in Cloud and HPC clusters. Beside the distributed and stateful compute nodes, stateless gateway nodes allow user interactions with the cluster. The two main challenges and open questions of DisResc are first the compilation of a time-based behaviour profile out of monitoring data, and second to define a distributed consensus algorithm for determining a best fitting node for a behaviour profile.

Griesinger, Frank; Seybold, Daniel; Domaschka, Jörg; Kritikos, Kyriakos; Woitsch, Robert
A DMN-based Approach for Dynamic Deployment Modelling of Cloud Applications
Service Oriented and Cloud Computing
September 2016
Seybold, Daniel; Woitsch, Robert; Domaschka, Jörg; Wesner, Stefan
BPaaS Execution in CloudSocket
Springer CCIS,
September 2016
Hauser, Christopher B.; Tsitsipas, Athanasios; Domaschka, Jörg
Context-Aware Cloud Topology Optimization for OpenStack
Springer CCIS,
September 2016
Seybold, Daniel; Domaschka, Jörg; Rossini, Alessandro; Hauser, Christopher B.; Griesinger, Frank; Tsitsipas, Athanasios
Experiences of models@run-time with EMF and CDO
ACM Digital Library,
August 2016
Rotta, Randolf; Nolte, Jörg; Nikolov, Vladimir; Schubert, Lutz; Bonfert, Stefan; Wesner, Stefan
MyThOS — Scalable OS Design for Extremely Parallel Applications
2016 Intl IEEE Conferences on Ubiquitous Intelligence Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People, and Smart World Congress (UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld),
Juli 2016

Klicken Sie hier um eine Übersicht aller Publikationen zu erhalten.