Scheduling of Time-Triggered Real-Time Systems
Constraints
Off-Line Computation of Real-Time Schedules Using Petri Nets
Discrete Event Dynamic Systems
Partial task assignment of task graphs under heterogeneous resource constraints
Proceedings of the 40th annual Design Automation Conference
From simulink to SCADE/lustre to TTA: a layered approach for distributed embedded applications
Proceedings of the 2003 ACM SIGPLAN conference on Language, compiler, and tool for embedded systems
Real-Time Systems: Scheduling, Analysis, and Verification
Real-Time Systems: Scheduling, Analysis, and Verification
Partitioning Real-Time Tasks among Heterogeneous Multiprocessors
ICPP '04 Proceedings of the 2004 International Conference on Parallel Processing
Task Partitioning upon Memory-Constrained Multiprocessors
RTCSA '05 Proceedings of the 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications
Handbook of Constraint Programming (Foundations of Artificial Intelligence)
Handbook of Constraint Programming (Foundations of Artificial Intelligence)
Solving a real-time allocation problem with constraint programming
Journal of Systems and Software
Multi-task Implementation of Multi-periodic Synchronous Programs
Discrete Event Dynamic Systems
Deterministic execution model on COTS hardware
ARCS'12 Proceedings of the 25th international conference on Architecture of Computing Systems
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The design of critical embedded real-time systems requires high confidence in the architecture and the implemented functionalities. Classically, such functions are supported on a single monoprocessor, behavior of which is completely predictable, while the execution is totally deterministic. With the growing complexity of systems, it becomes quite unavoidable to implement these systems on distributed architectures. Scaling from mono to multiprocessor raises several issues which we address in this paper: we propose a simple executive model based on time triggered paradigm and an automated approach to allocate real-time tasks based on constraint resolution techniques. We illustrate the method on an industrial case study.