Project Details
Projekt
GRK 1324: Model-based Development of Technologies for Self-organising Information Systems in Application for Disasters Management
Subject Area
Computer Science
Term
from 2006 to 2015
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 13124548
Information systems and underlying technologies for self-organising networks, in the context of a computer-supported disaster management, are the central topic of research for this Research Training Group. The research focusses on the important technologies needed at each individual node of a self-organising network. Research challenges within this Research Training Group include: finding a path through a network with the help of new routing protocols and forwarding techniques, replication of decentralised data, automated deployment and update of software components at runtime as well as work-load balancing among terminal devices with limited resources. Furthermore, non-functional aspects such as reliability, latency and robustness will be studied.
For this reason, the Research Training Group emphasises the use of techniques, methods, and concepts for designing and implementing geographic information systems on top of dynamic, highly flexible, self-organising networks and their integration with services for geographic information systems based on existing data base technologies in these areas.
Research in the suggested application domain is interdisciplinary by nature. A key differentiator of this Research Training Group is its model-based approach that will be applied to all layers of the system. Especially meta-model languages will aid disaster management experts to model their workflows, which may in turn be simulated in order to assess decision processes. Theoretical studies of workflow usability will provide the basis for investigations of the composability of partial workflows in complex scenarios. Workflows will also be studied for their applicability to aid the self-organisation of systems by dynamically allocating network resources. The combination of functional specification, automated code generation, and performance analysis methods is a distinguishing aspect of model based service engineering in self-organising distributed information systems, which will contribute significantly to the service quality of all system components.
For this reason, the Research Training Group emphasises the use of techniques, methods, and concepts for designing and implementing geographic information systems on top of dynamic, highly flexible, self-organising networks and their integration with services for geographic information systems based on existing data base technologies in these areas.
Research in the suggested application domain is interdisciplinary by nature. A key differentiator of this Research Training Group is its model-based approach that will be applied to all layers of the system. Especially meta-model languages will aid disaster management experts to model their workflows, which may in turn be simulated in order to assess decision processes. Theoretical studies of workflow usability will provide the basis for investigations of the composability of partial workflows in complex scenarios. Workflows will also be studied for their applicability to aid the self-organisation of systems by dynamically allocating network resources. The combination of functional specification, automated code generation, and performance analysis methods is a distinguishing aspect of model based service engineering in self-organising distributed information systems, which will contribute significantly to the service quality of all system components.
DFG Programme
Research Training Groups
Applicant Institution
Humboldt-Universität zu Berlin
Participating Institution
Fraunhofer-Institut für Rechnerarchitektur und Softwaretechnik (FIRST) (aufgelöst); Helmholtz-Zentrum Potsdam - Deutsches GeoForschungsZentrum (GFZ); Zuse-Institut Berlin (ZIB)
Spokesperson
Professor Dr. Joachim Fischer
Participating Researchers
Professorin Dr. Doris Dransch; Professor Johann-Christoph Freytag, Ph.D.; Professorin Dr. Verena V. Hafner; Professorin Dr. Tobia Lakes; Professor Dr. Ulf Leser; Professor Dr. Miroslaw Malek; Professor Dr. Jens-Peter Redlich; Professor Dr. Alexander Reinefeld; Professor Dr. Wolfgang Reisig; Professor Dr. Holger Schlingloff
