Systematic approaches to understanding and evaluating design trade-offs
Journal of Systems and Software
Computing robustness of FlexRay schedules to uncertainties in design parameters
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)
Search-based software engineering: Trends, techniques and applications
ACM Computing Surveys (CSUR)
Robustness analysis for battery-supported cyber-physical systems
ACM Transactions on Embedded Computing Systems (TECS)
Searching for the minimum failures that can cause a hazard in a wireless sensor network
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Proceedings of the 14th ACM SIGPLAN/SIGBED conference on Languages, compilers and tools for embedded systems
Robust and flexible mapping for real-time distributed applications during the early design phases
DATE '12 Proceedings of the Conference on Design, Automation and Test in Europe
Design synthesis and optimization for automotive embedded systems
Proceedings of the 2014 on International symposium on physical design
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Flexibility, the ability to adapt to change, is important for real-time systems. As in any type of system, changes arise from maintenance, enhancements and upgrades. These changes are only feasible if timing requirements imposed by the real-time nature of the system can still be met. A flexible design will allow tasks to be added without impinging on other tasks, causing them to miss deadlines. The design space for these systems consists of many configurations describing how tasks and messages are allocated to hardware and scheduled on a hardware platform. Heuristic search is a well recognised strategy for solving allocation and scheduling problems but most research is limited to finding any valid solution for a current set of requirements. The technique proposed here incorporates scenario based analysis into heuristic search strategies where the ability of a solution to meet a scenario is included as another heuristic for the changeability of a system. This allows future requirements to be taken into account when choosing a solution so that future changes can be accommodated with minimal alterations to the existing system.