Solving a real-time allocation problem with constraint programming

Pierre-Emmanuel Hladik (1) , Hadrien Cambazard (2) , Anne-Marie Déplanche (1) , Narendra Jussien (3)

1 IRCCyN - Institut de Recherche en Communications et en Cybernétique de Nantes
2 LINA - Laboratoire d'Informatique de Nantes Atlantique
3 TASC - Theory, Algorithms and Systems for Constraints

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.

Domaines: Intelligence artificielle [cs.AI]; Recherche opérationnelle [math.OC]

Pierre-Emmanuel Hladik, Hadrien Cambazard, Anne-Marie Déplanche, Narendra Jussien. Solving a real-time allocation problem with constraint programming. Journal of Systems and Software, 2007, 81 (1), pp.132-149. ⟨10.1016/j.jss.2007.02.032⟩. ⟨hal-00293898⟩