Towards a Parallel Constraint Solver for Cloud Computing Environments

This paper presents a parallel Constraint Programming (CP) solver for Optimizing the Performance of CP problems in Cloud Computing Environments. The parallelization of Constraint Programming (CP) solvers is widely proposed in the literature to improve the resolution of CP problems by reducing the computing time. Moreover, the current CP problems addressed by the industry involve big data scenarios and solving such complex problems in less time require the use of scalable many-core computing resources that are easily offered by the cloud computing environments. However, achieving optimal performance on CP solvers is a major concern while dealing with cloud infrastructure. To address this issue, we propose a parallelization approach that enables communication between several parallel CP solvers to efficiently exploit the massively available computing resources, thus minimizing the performance degradation of the CP solvers in cloud environments. The benefit of employing our approach is insuring good load balancing between all computing cores that encompasses the cloud infrastructure.