Dynamically Scheduling Deadline-Constrained Interleaved Workflows on Heterogeneous Computing Systems

Heterogeneous computing systems are extensively utilized to execute a wide range of time-critical services, which encompass numerous interdependent tasks organized in the form of workflows. In practice, the dynamic arrival of workflows often interleaves with their execution, leading to resource contention among multiple workflows and potentially causing QoS (Quality of Service) degradation. However, compared to the extensive research on single workflow scheduling, interleaved workflow scheduling has received relatively less attention. Moreover, the challenge of effectively scheduling limited computing resources to promptly complete consecutively arriving workflows remains underexplored, despite its practical importance. To fill this gap, this work proposes a method called Urgency-based List Scheduling (ULS) for dynamically scheduling deadline-constrained interleaved workflows. In ULS, a novel task property called urgency is introduced to prioritize tasks from multiple workflows by capturing real-time execution information, and each newly arrived workflow is scheduled with the outstanding tasks of prior workflows based on a list-based strategy to make more informed decisions. Extensive evaluation experiments are performed and the findings illustrate that ULS can achieve a reduction of at least 68% in deadline miss rates and 77% in overall tardiness compared to existing methods.