Fixed-Priority Sensitivity Analysis for Linear Compute Time Models
IEEE Transactions on Software Engineering
Measuring the Robustness of a Resource Allocation
IEEE Transactions on Parallel and Distributed Systems
A General Framework for Analysing System Properties in Platform-Based Embedded System Designs
DATE '03 Proceedings of the conference on Design, Automation and Test in Europe - Volume 1
ICDCS '05 Proceedings of the 25th IEEE International Conference on Distributed Computing Systems
A Formal Approach to Multi-Dimensional Sensitivity Analysis of Embedded Real-Time Systems
ECRTS '06 Proceedings of the 18th Euromicro Conference on Real-Time Systems
Methods for multi-dimensional robustness optimization in complex embedded systems
EMSOFT '07 Proceedings of the 7th ACM & IEEE international conference on Embedded software
Distributed Performance Control in Organic Embedded Systems
ATC '08 Proceedings of the 5th international conference on Autonomic and Trusted Computing
System level performance analysis for real-time automotive multicore and network architectures
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Computing robustness of FlexRay schedules to uncertainties in design parameters
Proceedings of the Conference on Design, Automation and Test in Europe
Robust design of embedded systems
Proceedings of the Conference on Design, Automation and Test in Europe
Optimization of task allocation and priority assignment in hard real-time distributed systems
ACM Transactions on Embedded Computing Systems (TECS)
Sensitivity analysis for arbitrary activation patterns in real-time systems
Proceedings of the Conference on Design, Automation and Test in Europe
Multi-mode monitoring for mixed-criticality real-time systems
Proceedings of the Ninth IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis
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Embedded system optimization typically considers objectives such as cost, timing, buffer sizes and power consumption. Robustness criteria, i.e. sensitivity of the system to variations of properties like execution and transmission delays, input data rates, CPU clock rates, etc., has found less attention despite its practical relevance.In this paper we introduce robustness metrics and propose an algorithm considering these metrics in design space exploration and system optimization. The algorithm can optimize for static and for dynamic robustness, the latter including system or designer reactions to property variations. We explain several applications ranging from platform optimization to critical component identification.By means of extensive experiments we show that design space exploration pursuing classical design goals does not necessarily yield robust systems, and that our method leads to systems with significantly higher design robustness.