Dynamic binding and scheduling of firm-deadline tasks on heterogeneous compute resources

Embedded systems increasingly include heterogeneous compute resources. Yet the vast majority of real-time scheduling methods are designed for single-resource or homogeneous multi-resource systems. Heterogeneity complicates scheduling; task execution time is resource-dependent. Furthermore, the best resource for one task may not necessarily be the best resource for all tasks, so one resource may not be universally more valuable than another. This paper presents new algorithms designed specifically for heterogeneous real-time scheduling. We evaluate the algorithms' deadline miss rates for heterogeneous task sets that represent a variety of execution scenarios, and show that two of our algorithms have lower deadline miss rates than the Earliest Deadline First or Least Laxity First approaches. We also discuss how task set and system characteristics affect the schedulers' abilities to achieve a quality schedule.