Hierarchical planning is used to group applications based on their functionality to improve resource aggregation and temporary isolation between applications. The task criticality factor is used to compare tasks with the cores in a subsystem cluster. Tasks with high criticality are statically compared with specific kernels for assurance of determinism, while lower criticality tasks allow you to transfer through the cores in a cluster to improve performance. Adaptive hierarchical planning on fuzzy logic for periodic real-time tasks is an approach in which a heuristic method based on fuzzy logic is used to enable the system to adapt. This article presents the results of the obtained approach of hierarchical planning, when the planning of subsystems is corrected on the basis of the level of criticality, and not just the strictly established term. The result is an integrated system that is better suited to adapt to computational variations, providing time guarantees for tasks with high criticality, which provides a minimum level of service to reduce criticality requirements. A practical application for sharing resources in hierarchical planning systems is actual equipment based on aerospace equipment in the simulation of cycles. Protocols for resource synchronization based on pre-emptive and predicted resources were used in the simulation and proved to be effective in improving response time and eliminating time-misses for hard real-time tasks compared to traditional resource synchronization protocols.
hierarchical planning, built-in system, resource synchronization protocol, adaptive planning