Automatic Optimization of Redundant Message Routings in Automotive Networks

To cope with the strict reliability requirements of safety-critical ADAS applications, the upcoming TSN standard introduces mechanisms that enable transmission redundancy at any switch or end node. However, it is up to the designer to decide at which points and for which messages to activate transmission redundancy. This significantly increases the design space and requires to trade-off reliability with other routing-related design objectives like network load, transmission timing, or the monetary cost of the hardware. As a remedy, this paper a) presents two different exact approaches to generate feasible redundant message routings and b) proposes an extension of the state-of-the-art approach for the multi-objective routing optimization, enabling the optimizer to directly adjust system features that are relevant for the design objectives. A case study with an application from the automotive domain compares the optimization capabilities of the presented approaches for the routing generation and demonstrates the significant gain in optimization power that is achieved with the proposed optimization extension.

[1]  Marco Laumanns,et al.  Combining Convergence and Diversity in Evolutionary Multiobjective Optimization , 2002, Evolutionary Computation.

[2]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[3]  Martin Lukasiewycz,et al.  SAT-decoding in evolutionary algorithms for discrete constrained optimization problems , 2007, 2007 IEEE Congress on Evolutionary Computation.

[4]  Martin Lukasiewycz,et al.  Symbolic Reliability Analysis and Optimization of ECU Networks , 2008, 2008 Design, Automation and Test in Europe.

[5]  Martin Lukasiewycz,et al.  Combined system synthesis and communication architecture exploration for MPSoCs , 2009, 2009 Design, Automation & Test in Europe Conference & Exhibition.

[6]  Soonhoi Ha,et al.  A Systematic Design Space Exploration of MPSoC Based on Synchronous Data Flow Specification , 2010, J. Signal Process. Syst..

[7]  Martin Lukasiewycz,et al.  Opt4J: a modular framework for meta-heuristic optimization , 2011, GECCO '11.

[8]  Michael Glaß,et al.  Symbolic System Synthesis Using Answer Set Programming , 2013, LPNMR.

[9]  Michael Glaß,et al.  Timing analysis of Ethernet AVB-based automotive E/E architectures , 2013, 2013 IEEE 18th Conference on Emerging Technologies & Factory Automation (ETFA).

[10]  Michael Glaß,et al.  Towards scalable symbolic routing for multi-objective networked embedded system design and optimization , 2014, 2014 International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS).

[11]  Martin Lukasiewycz,et al.  System simulation and optimization using reconfigurable hardware , 2014, 2014 International Symposium on Integrated Circuits (ISIC).

[12]  Frank Dürr,et al.  Time-sensitive Software-defined Network (TSSDN) for Real-time Applications , 2016, RTNS.

[13]  Michael Glaß,et al.  Formal reliability analysis of switched Ethernet automotive networks under transient transmission errors , 2016, 2016 53nd ACM/EDAC/IEEE Design Automation Conference (DAC).

[14]  Michael Glaß,et al.  Optimizing message routing and scheduling in automotive mixed-criticality time-triggered networks , 2017, 2017 54th ACM/EDAC/IEEE Design Automation Conference (DAC).

[15]  Michael Glaß,et al.  Formal timing analysis of non-scheduled traffic in automotive scheduled TSN networks , 2017, Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017.

[16]  Andy D. Pimentel,et al.  A Generic Infrastructure for System-level MP-SoC Design Space Exploration , .