Improving scheduling performance of a real-time system by incorporation of an artificial intelligence planner
- Jesus Fernandez-Conde 1
- Pedro Cuenca-Jimenez 1
- Rafael Toledo-Moreo 2
- 1 Universidad Rey Juan Carlos, Madrid, Spain
- 2 Universidad Politécnica de Cartagena, Spain
- José Manuel Ferrández Vicente (dir. congr.)
- José Ramón Álvarez-Sánchez (dir. congr.)
- Félix de la Paz López (dir. congr.)
- Javier Toledo Moreo (dir. congr.)
- Hojjat Adeli (coord.)
Editorial: Springer Suiza
ISBN: 978-3-030-19651-6
Año de publicación: 2019
Páginas: 127-136
Tipo: Capítulo de Libro
Resumen
Scheduling is one of the classic problems in real-time systems.In real-time adaptive applications, the implementation of somesort of run-time intelligence is required, in order to build real-time intelligent systems capable of operating adequately in dynamic and complex environments. The incorporation of artificial intelligence planning techniques in a real-time architecture allows the on-line reaction to external and internal unexpected events. In this work a layered architecture integrating real-time scheduling and artificial intelligence planning techniques has been designed, in order to implement a real-time scheduler with capability to perform effectively in these scenarios. This multi-levelscheduler has been implemented and evaluated in a simulated information access system destined to broadcast information to mobile users.Results show that incorporation of artificial intelligence to the real-time scheduler improves the performance, adaptiveness and responsiveness of the system.