In order to solve the hybrid and dependent task scheduling and critical source allocation problems, a task scheduling algorithm has been developed by first presenting the tasks, and then describing the hybrid and depe...In order to solve the hybrid and dependent task scheduling and critical source allocation problems, a task scheduling algorithm has been developed by first presenting the tasks, and then describing the hybrid and dependent scheduling algorithm and deriving the predictable schedulability condition. The performance of this agorithm was evaluated through simulation, and it is concluded from the evaluation results that the hybrid task scheduling subalgorithm based on the comparison factor can be used to solve the problem of aperiodic task being blocked by periodic task in the traditional operating system for a very long time, which results in poor scheduling predictability; and the resource allocation subalgorithm based on schedulability analysis can be used to solve the problems of critical section conflict, ceiling blocking and priority inversion; and the scheduling algorithm is nearest optimal when the abortable critical section is 0.6.展开更多
文摘In order to solve the hybrid and dependent task scheduling and critical source allocation problems, a task scheduling algorithm has been developed by first presenting the tasks, and then describing the hybrid and dependent scheduling algorithm and deriving the predictable schedulability condition. The performance of this agorithm was evaluated through simulation, and it is concluded from the evaluation results that the hybrid task scheduling subalgorithm based on the comparison factor can be used to solve the problem of aperiodic task being blocked by periodic task in the traditional operating system for a very long time, which results in poor scheduling predictability; and the resource allocation subalgorithm based on schedulability analysis can be used to solve the problems of critical section conflict, ceiling blocking and priority inversion; and the scheduling algorithm is nearest optimal when the abortable critical section is 0.6.
