STRATEGIES FOR SCHEDULING OPTIONAL TASKS IN INTELLIGENT REAL-TIME ENVIRONMENTS

Control systems have been the main application field of real-time syst em programming. While the complexity of the control system has been so lved using classical theory, the theory to design the real-time system has follow some well known practices. However, when the complexity of the applications requires the combination of the control theory and t echniques coming from the artificial intelligence field, the real-time design and implementation requires some new features. One of the main aspects to be considered is the non predictable behaviour of most of these techniques and, as consequence, their application to systems whe re the predictability plays a critical role. In this paper, a global o rganisation of a real time artificial intelligence system is presented . The proposal includes a task model to define real time tasks with co mponents where the execution time is unbounded. To handle these tasks, a system organisation is proposed. The system includes an intelligent server that manages the execution of all unbounded parts. The proposa l uses two scheduling levels, a static first level which is supported directly by the operating system, and a dynamic second level which han dles the optional parts. Several scheduling algorithms are presented a nd evaluated.