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|<div style="text-align:left;font-size:18pt;color:#6687a7"><font style="color:#00376c;font-size:24pt;font-face:bold">METRIK - </font> Model-Based Development of Technologies for Self-Organizing Decentralized Information Systems in Disaster Management</div> <br /><br /> <div style="text-align:right">[[Hauptseite|Informationen über dieses Graduatiertenkolleg auf Deutsch]]</div>
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===Recent Information===
* Our [[Forschungsseminar|research seminar]] has a new date (Thu, 3pm c.t.)
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Recent progress in basic research has lead to visions how to use new self-organizing networks for advanced information systems. These networks function without central administration – all nodes are able to adapt themselves to new environments autonomously and independently. The addition of new nodes or failure of individual nodes does not significantly impact the network’s ability to function properly. Information systems and underlying technologies for self-organizing networks, in the context of a specific application domain, are the central topic of research for this graduate school.

The research focuses on the important technologies needed at each individual node of a self-organizing network. Research challenges within this graduate school include: finding a path through a network with the help of new routing protocols and forwarding techniques, replication of decentralized 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.

[[Bild:Mission.jpg|left|Distributed, self-organizing networks for disaster management]]
The graduate school’s focus on decentralized information systems with self-organizing networks is sharpened by relating those more general research issues to a very specific application domain: computer-supported disaster management. For this reason, the graduate school emphasizes the use of techniques, methods, and concepts for designing and implementing geographic information systems on top of dynamic, highly flexible, self-organizing networks and their integration with services for geographic information systems based on existing technologies in these areas. To manage the complexity of data, information, and services and to make them available for the user, it is extremely important to hide (as much as possible) the difficulties and the complexity of such an environment. Only if we succeed in shielding the user from internal errors and/or changes, such systems will be accepted.

Aside from the specific demands given by the geographically dispersed positions in our application domain, the network topology plays an important role in the configuration process, because the partitioning into separated sub-networks must be detected and prevented. Furthermore, if the network should have been partitioned, it must be possible to find all sub-networks and reconnect them – if possible – with a minimal number of links.

Research in the suggested application domain is interdisciplinary by nature. The graduate school will conduct basic research in applying workflow management technology to disasterous events, such as earth quakes, based on the developed network protocols and information service concepts. The goal of this work to support decision makers in making better informed decisions by using the complete range of available options.

A key differentiator of this graduate school is its model-based approach that will be applied to all layers of the system. 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-organization 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-organizing distributed information systems, which will contribute significantly to the service quality of all system components.

==Application Procedure==
Humboldt-Universität Berlin recently started a joint project for
model-based development of self-organizing information systems in
catastrophe management. We are seeking a number of talented and
enthusiastic PhD students in the following areas:

* distributed and heterogeneous databases
* network algorithms and routing
* workflow, especially ad-hoc and scientific workflow
* geospatial information systems

We require an excellent Master (equivalent to a German Diplom) in computer
science or in geography with a specialization in geospatial information
systems. Candidates must have a profound knowledge of German and must
provide references from at least two internationally renown researchers.
Successful candidates will be granted a fellowship of approximately 1300
Euro per month for 2-3 years. Please apply by 30 november 2007 using the
following URL:

[http://metrik.informatik.hu-berlin.de/grk-wiki/index.php/Bewerbungsprozedur http://metrik.informatik.hu-berlin.de/grk-wiki/index.php/Bewerbungsprozedur]

The project combines researchers from computer science and geography. It
is carried by five institutions: Humboldt-Universität zu Berlin,
Fraunhofer Institute for Software Architecture and Engineering, the
Zuse-Institute for Scientific Computing, the Hasso-Plattner Institute for
Software Engineering, and the Geospatial Research Centre Potsdam. The
project is funded by the German Research Council.