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IEEE Transactions on Software Engineering
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IEEE Transactions on Computers
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Constraints
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CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
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INFORMS Journal on Computing
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APSEC '00 Proceedings of the Seventh Asia-Pacific Software Engineering Conference
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EUROMICRO '98 Proceedings of the 24th Conference on EUROMICRO - Volume 2
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The Knowledge Engineering Review
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RTAS '04 Proceedings of the 10th IEEE Real-Time and Embedded Technology and Applications Symposium
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Handbook of Constraint Programming (Foundations of Artificial Intelligence)
Handbook of Constraint Programming (Foundations of Artificial Intelligence)
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IEEE Transactions on Software Engineering
EURO-PDP'00 Proceedings of the 8th Euromicro conference on Parallel and distributed processing
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CBSE'05 Proceedings of the 8th international conference on Component-Based Software Engineering
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FORMATS '08 Proceedings of the 6th international conference on Formal Modeling and Analysis of Timed Systems
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GREENCOM-CPSCOM '10 Proceedings of the 2010 IEEE/ACM Int'l Conference on Green Computing and Communications & Int'l Conference on Cyber, Physical and Social Computing
ScatterD: Spatial deployment optimization with hybrid heuristic/evolutionary algorithms
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
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In this paper, we present an original approach (CPRTA for ''Constraint Programming for solving Real-Time Allocation'') based on constraint programming to solve a static allocation problem of hard real-time tasks. This problem consists in assigning periodic tasks to distributed processors in the context of fixed priority preemptive scheduling. CPRTA is built on dynamic constraint programming together with a learning method to find a feasible processor allocation under constraints. Two efficient new approaches are proposed and validated with experimental results. Moreover, CPRTA exhibits very interesting properties. It is complete (if a problem has no solution, the algorithm is able to prove it); it is non-parametric (it does not require specific tuning) thus allowing a large diversity of models to be easily considered. Finally, thanks to its capacity to explain failures, it offers attractive perspectives for guiding the architectural design process.