Department of Computer Science 7
Research
A focus of our work is quality-of-service (QoS) of networked systems. Quality-of-service is understood as an umbrella covering various aspects such as traditional performance measures
(e.g., throughput of a network, system response time, loss rate, etc.) and dependability measures (e.g., reliability of a network, availability of a server system, etc.)
but also real time, safety, security, energy, and economics. For this purpose we apply various kinds of modeling, simulation, analysis, test and measurements and we also develop specialized
tools. As a specific approach we are also developing test-driven agile simulation, in which UML-based simulation is combined with model-based testing. Currently we are dealing with a
number of different applications: car communications, industrial communications, sensor-actuator networks, audio communications, as well as energy and health care.
Car Communications
As many electronic control unit (ECUs) communicate in today cars (by using CAN, FlexRay, and Ethernet), we work on designing such architectures by means of analysis and simulation. We also work on test benches and systematic testing methods for quality assurance. This work is often performed in the context of INI.FAU. We also have designed a framework in which traffic simulation is coupled with network simulation to allow for a thorough investigation of different aspects of vehicular communications.
Industrial Communications
Specialized busses as well as Ethernet are common communication technologies in automation and both need to satisfy specific requirements, e.g., for the latencies of sent messages. Besides simulation models for wireless communications according to IEEE 802.15.4 and ZigBee we use network calculus as an analytic approach for establishing real-time guarantees in wired communications.
Energy
In the area of energy research, we contribute to the energy system of the future in the Energie Campus Nürnberg (EnCN). Renewable energy generation is fluctuating, the mismatch between offer and demand can be resolved either by control of conventional power plants, by energy storage or by shifting load peaks on the demand side. The growth of renewables also needs more decentralized coordinated units (e.g. in houses or communities) instead of large centralized ones. For the complete system of merging electrical and communication networks, of various storage technologies and the remaining efficient usage of fossil fuels, simulation models are being developed: on a smaller scale for microgrids (combined producers and consumers which try to remain self-sufficient) and on a larger scale for the main aspects of the energy system of a complete region like a state.
Health Care
We develop simulation models for an early prediction of implications of new medical technologies and processes and vice versa for an identification of potential innovations for desired effects. For this purpose, hybrid models based on the system dynamics and agent-based modeling paradigms are being developed and parameterized by empirical data. Agents represent patients and medical workflows and are embedded in system dynamic models which represent aspects like demography, economy, and epidemiology. Medical technologies are represented by quantitative parameters. Outcomes are epidemiologic and health economics parameters such as expected improvement of life quality or reduction of incidence. This work is performed mainly in the context of ProHTA (Prospective Health Technology Assessment) within the Cluster of Excellence for Medical Technology – Medical Valley European Metropolitan Region Nuremberg (EMN).
Test-Driven Agile Simulation
Test-driven agile simulation combines simulation and model-based testing in order to provide mutual benefits for both and in order to define a new approach for systems engineering with improved quality assurance. For this purpose system models and test models with a user perspective (usage models for short) are being developed in parallel and iteratively. The complete approach is based on the UML2.
System models are described by class, composite structure, state, and activity diagrams and can be extended by quantitative aspects (e.g., deterministic or stochastic execution times, routing probabilities) by using the MARTE profile (Modeling and Analysis of Real-Time and Embedded Systems)‏ for UML. Such a system model is compiled into C++ and executed be means of the network simulator OMNeT++, results are finally fed back on the UML system model level. From the perspective of simulation, the advantage compared with other proprietary simulators is that simulation models can be developed in an open format. From the perspective of systems engineering, the advantage is that system models can be executed early in a simulation environment. A further advantage is that with the system model quantitative assessments become possible as well.
Independent from this, usage models can be developed as a basis for testing. Here state and sequence diagrams are being used, which describe selected usages of the system or portions of the system. Usage models are no system models and just represent possible inputs and expected outputs. Usage models can be extended by Markov profiles to describe usage frequencies. From the usage model it is possible to derive test cases by various strategies, the test cases plus the relevant portions of the system model are then also executed on the OMNeT++ level and lead to common test verdicts like passed, failed, etc. From the perspective of testing, the advantage is that test cases can be executed early in a simulation environment and that both system and test model can be validated and iterated. From the perspective of simulation, the advantage is that a systematic approach is available to validate simulation models.
Code being generated from such a system model is on a higher quality level and the test cases on the simulation level can also be used for it, which is then the system under test. This approach can be integrated with various development models such as the V model or agile development.
A. Djanatliev, W. Dulz, R. German, and V. Schneider., VeriTAS - A Versatile Modeling Environment for Test-driven Agile Simulation. Proceedings of the 2011 Winter Simulation Conference, December 2011.
Groups