Azad Mohammed Shaik
It is critical to prioritize tasks in an RTOS for safe and efficient operation of the system. Many engineers utilize informal ad hoc techniques to assign task priorities, resulting in missed deadlines, priority inversions, and potentially catastrophic failures in safety-critical areas. This paper introduces the Criticality Urgency Quadrant Model (QUADRANT), a systematic two-dimensional model for classification and assignment of task priorities with orthogonal axes of urgency and criticality. QUADRANT is intended to give practitioners on standard fixed-priority RTOS platforms without formal mixed criticality analysis infrastructure a lightweight, deployable engineering heuristic. The model has been validated through empirical tasks executed with FreeRTOS (POSIX simulation, Linux 5.15, Intel Xeon) and 16 concurrent tasks performing 300,000 iterations of CPU stress workloads over a 120 second time frame, ultimately producing results that can be compared against Rate Monotonic Scheduling (RMS), Deadline Monotonic Scheduling (DMS), Audsley’s Optimal Priority Assignment (OPA) Method using Response Time Analysis (RTA) and ad hoc. Key results indicated that QUADRANT executed with zero deadline misses across all task quadrants under normal conditions, while ad hoc produced 769 total deadline misses (653 Q1); DMS produced 229 misses; RMS produced 688 total deadline misses; the majority of which were located in the critical Q2 monitor, while OPA/RTA declared the task set un-schedulable due to priority scarcity (16 tasks, 10 priorities). This emphasizes a known characteristic of worst-case analysis: the lack of comparability with the average case for performance. OPA and QUADRANT serve different needs as complementary tools, not as competitive algorithms. Additionally, the evaluation performed through three-level stress testing (baseline 45 seconds, rigorous 90 seconds, heavy 120 seconds) and 122,000 total task executions validates graceful degradation under overload conditions. QUADRANT produced 26 minor Q2 misses (0.065% failure rate) under maximum load; while RMS produced 532 Q2 misses and ad hoc produced 12,470 Q2 misses, evidencing superior assignment and execution of task priorities. The results on the POSIX simulation platform are valid; though actual execution timing may be different when executed on bare-metal targets, the relative effectiveness of priority assignment can be easily replicated between platforms. All source code of the open-source FreeRTOS implementations is provided for reproducible research and adoption within automotive, medical, and aerospace industries.