%0 Book %1 annighoefer2014e %A Annighöfer, Bjoern %A Thielecke, Frank %B 33rd Digital Avionics System Conference %C Colorado Springs, CO, USA %D 2014 %K imported myown nonils %R 10.1109/DASC.2014.6979461 %T Network Topology Optimization for Distributed Integrated Modular Avionics %U http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6979461 %X This paper shows how to optimally generate Aircraft Data and Communication Network (ADCN) topologies based on the message flows and network component characteristics within Integrated Modular Avionics (IMA). A novel algorithm for multi- objective network topology optimization is presented. This algorithm can derive an optimal network topology that hosts all signals and respects possible bandwidth and safety limitations. The derived topology includes switches, switch locations, and interconnections. From all feasible topologies, the presented algorithm calculates the best trade-off solutions for multiple objectives (the so-called Pareto optimum) using combinatorial optimization. The solutions are globally optimal. To reduce the problem size and calculation time for large-scale architectures a variant of the algorithm using pre-calculated paths is proposed in addition. Both algorithms are demonstrated by calculating optimal AFDX networks for a small A320-like and a large A380-like scenario minimizing weight and Operational Interruption Cost (OIC). Results show significant optimization potential compared to manually designed networks and reveal interesting relations between functional mappings and network topologies.

@book{annighoefer2014e, abstract = {This paper shows how to optimally generate Aircraft Data and Communication Network (ADCN) topologies based on the message flows and network component characteristics within Integrated Modular Avionics (IMA). A novel algorithm for multi- objective network topology optimization is presented. This algorithm can derive an optimal network topology that hosts all signals and respects possible bandwidth and safety limitations. The derived topology includes switches, switch locations, and interconnections. From all feasible topologies, the presented algorithm calculates the best trade-off solutions for multiple objectives (the so-called Pareto optimum) using combinatorial optimization. The solutions are globally optimal. To reduce the problem size and calculation time for large-scale architectures a variant of the algorithm using pre-calculated paths is proposed in addition. Both algorithms are demonstrated by calculating optimal AFDX networks for a small A320-like and a large A380-like scenario minimizing weight and Operational Interruption Cost (OIC). Results show significant optimization potential compared to manually designed networks and reveal interesting relations between functional mappings and network topologies.}, added-at = {2017-03-24T09:40:30.000+0100}, address = {Colorado Springs, CO, USA}, author = {Annighöfer, Bjoern and Thielecke, Frank}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/23aab3085e034b0df6adee0bca8e70e2b/annighoefer}, booktitle = {33rd Digital Avionics System Conference}, doi = {10.1109/DASC.2014.6979461}, file = {:Annighoefer - Network Topology Optimization for Distributed Integrated Modular Avionics.pdf:PDF}, groups = {Avionics Optimization}, interhash = {9d2698080b9993770935e2a3267e875d}, intrahash = {3aab3085e034b0df6adee0bca8e70e2b}, keywords = {imported myown nonils}, month = {October}, owner = {bjoern}, timestamp = {2020-01-27T08:55:37.000+0100}, title = {Network Topology Optimization for Distributed Integrated Modular Avionics}, url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6979461}, year = 2014 }