Abstract

The complexity of embedded real-time systems has increased, and most applications have large diversity in execution times of their tasks. Therefore, most traditional scheduling techniques do not satisfy requirements of such applications. This article proposes an adaptive hierarchical scheduling framework for a set of independent concurrent applications composing of soft and hard real time tasks, that run on a single processor. It ensures temporal partitioning between independent applications with budget adaption feature, where CPU time of each application is periodically and dynamically assigned. Implemented in the kernel of TI-RTOS on a resource constrained platform, experiments show that proposed scheme provides good performance for multiple applications with dynamic tasks under overload conditions. Compared with traditional priority scheduler originally implemented in TI-RTOS and EDF scheduler, it achieves low miss ratio with minimal overhead while yielding temporal partitioning.

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