Real-Time Uniprocessor - Scheduler Simulator

A simulator for scheduling algorithms commonly used in real-time operating systems, including:

1. Rate Monotonic (RM)
2. Deadline Monotonic (DM)
3. Earliest-Deadline First (EDF)
4. Round Robin (RR)
5. Audsley’s Algorithm

The simulator assesses task schedulability based on attributes like offset, computation time, deadline, and period.

How to Run

python3 main.py {rm|dm|audsley|edf|rr} <task_set_file|task_set_directory> [options]

Parameters

Algorithm: Choose one of rm, dm, audsley, edf, or rr.

Task Set: Provide a path to either a single task set file or a directory of task set files for batch processing.

Options:

• -v or --verbose: Enable detailed output, showing the full schedule if a simulation is run.
• -f or --force_simulation: Force full simulation even if shortcuts (like utilization checks) are available.

Task Set File Format

Each task is represented by four parameters: O: Offset C: Computation time D: Deadline T: Period

Tasks are added with their respective offset 𝑂𝑖, computation time 𝐶𝑖, deadline 𝐷𝑖 and period 𝑇𝑖. Task set files are simple Comma Separated Value (CSV) files where the line 𝑖 encodes the 𝑂𝑖,𝐶𝑖,𝐷𝑖,𝑇𝑖 of task 𝑖.

0,7,41,58
1,4,62,69
4,3,12,80
0,8,24,94

Project Structure

• simulator.py: Main entry point to run the simulations.
• algorithms.py: Contains the classes for each scheduling algorithm.
• entities.py: Defines core data structures like TaskSet and Task.
• helpers.py: Utility functions for feasibility checks, utilization, and other calculations.
• plotters.py: Functions to visualize results and performance of different algorithms.

Example

To run the simulator with Deadline Monotonic scheduling on a specific task set file:

python3 main.py dm path/to/task_set.csv -v

Additional Features

Batch Processing: If a directory of task set files is provided, the simulator will process all files in parallel and generate aggregate statistics.

Visualization: The plotters.py module includes methods to visualize success rates and feasibility ratios for different algorithms, especially useful when comparing performance across multiple task sets.