Algoritmo genético permutacional para el despliegue y la planificación de sistemas de tiempo real distribuidos

The deployment and scheduling of tasks and messages in distributed real-time systems are NP-hard problems, so there are no optimal methods to solve them in polynomial time. Consequently, these problems are suitable to be approached with generic search and optimisation algorithms. In this paper we propose a multi-objective genetic algorithm based on a permutational solution encoding for the deployment and scheduling of distributed real-time systems. Besides deploying and scheduling tasks and messages, the algorithm can minimize the number of the used computers, the utilization of computing and networking resources and the average worst-case response times of the applications. The experiments show that this genetic algorithm can successfully synthesize complex distributed real-time systems in reasonable times.

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