For more than 25 years extensive software/hardware research and development efforts had been devoted to problems in real-time, safety-critical, and embedded systems. Security and safety issues were considered crucial in mission-critical systems. While all such constraints had been derived as design problems in software control systems for real-world applications, they were treated as separate aspects since each of them proved even difficult enough even when studied separately. While this resulted gradually in nearly different scientific disciplines it turned out to be increasingly inadequate for the construction of large control systems, in particular for applications with (partially) autonomous entities and decision-making: As a well-known example, optimal real-time performance may well be adverse to optimal overall throughput, and vice versa.
Traditional approaches for modeling and analyzing self-organizing process systems (e.g. optimization or other classical theoretical methods) normally fall short concerning efficient solutions in practice. They often do not really scale: With a growing system size, the computation time may well explode considering also real-time constraints.
In several novel application areas like smart power grids, renewable energy and electric power management, routing in today’s and future Internet applications, transportation planning or traffic control systems in logistics, smart health-care systems, Internet-of-Things, interconnected and collaborative intelligent mobility solutions, and self-driving vehicles, novel technological developments have posed a class of novel cross-disciplinary R&D themes where modeling, implementing, analyzing, and systematically experimenting by incorporating simulative approaches require a very close collaboration between researchers and developers in the disciplines involved. Solutions have been pursued, and even implemented, which borrow principles from Natural Computing, Swarm Intelligence, and Simulation Engineering. Also, they replace conventional approaches issuing exact solutions, which are practically irrelevant, through iterative and adaptive methods which are faster to obtain and at the same time of top quality (Self-Organizing Maps). Open problems such as on-line organization, consistency, self-adaptiveness, and availability of mobile and dynamic geographic data (in outer space, in wide-spread maritime operations etc.) have been identified as particular candidates for self-organizing research among many others.
For all such questions and problems, hardware and software aspects need to be jointly considered and studied. The proposed session addresses the following domains and methods:
Karl-Erwin Großpietsch Euromicro
Konrad Kloeckner Euromicro
(to be announced)