Schedulability Bounds for Parallel Real-Time Tasks under Global Rate-Monotonic Scheduling

TL;DR

This paper introduces new schedulability bounds for parallel real-time tasks under Global Rate-Monotonic scheduling, incorporating workload graph structure via the tensity metric, and improves capacity bounds significantly.

Contribution

It develops the first utilization-tensity bound for G-RM and enhances the capacity augmentation bound from 3.73 to 3.18, advancing theoretical and practical understanding.

Findings

New utilization-tensity schedulability bound for G-RM

Improved capacity augmentation bound to 3.18

Outperforms existing bounds in experiments

Abstract

Schedulability bounds not only serve as efficient tests to decide schedulability of real-time task systems but also reveal insights about the worst-case performance of scheduling algorithms. Different from sequential real-time task systems for which utilization is a suitable metric to develop schedulability bounds, schedulability of parallel real-time tasks depends on not only utilization but also the workload graph structure of tasks, which can be well represented by the tensity metric. In this paper, we develop new analysis techniques for parallel real-time task systems under Global Rate-Monotonic (G-RM) scheduling and obtain new results on schedulability bounds based on these two metrics: utilization and tensity. First, we develop the first utilization-tensity bound for G-RM. Second, we improve the capacity augmentation bound of G-RM from the best known value 3.73 to 3.18. These schedulability bounds not only provide theoretical insights about real-time performance of G-RM, but also serve as highly efficient schedulability tests, which are particularly suitable to design scenarios in which detailed task graph structures are unknown or may change at run-time. Experiments with randomly generated task sets show that our new results consistently outperform the state-of-the-art with a significant margin under different parameter settings.