Operating System Process Scheduling Experiment Design

Experimental Objectives and Significance

Process scheduling is a core function of an operating system, directly affecting system performance and resource utilization. Through this experiment, students will deeply understand the basic principles of process scheduling, master the implementation methods of different scheduling algorithms, and analyze performance differences through actual testing. The experimental objectives include:

• Verify the fairness and efficiency of scheduling algorithms
• Familiarize with process state transitions and scheduling mechanisms
• Develop an understanding of operating system kernel design

Related Knowledge Points

Process Scheduling Basics

Process Scheduling is the process by which an operating system decides which process obtains CPU resources based on priority, time slices, etc. Process states include ready, running, blocked, and terminated states, and the scheduler switches between these states.

Common Scheduling Algorithms

1. First-Come, First-Served (FCFS)
   • Schedules processes in the order of their arrival, which is simple but may lead to long waiting times.
2. Shortest Job First (SJF)
   • Prioritizes processes with the shortest estimated execution time, reducing average waiting time.
3. Priority Scheduling
   • Decides execution order based on process priority, with high-priority processes executed first.
4. Round-Robin (RR)
   • Assigns CPU resources in a round-robin manner to each process, avoiding long blocking periods.

Experiment Environment Configuration

• Operating System: Linux (e.g., Ubuntu 20.04) or Windows 10
• Development Tools: GCC compiler, GDB debugger, Valgrind performance analysis tool
• Hardware Requirements: At least 8 GB memory, multi-core CPU (for simulating multi-process scenarios)

Experimental Steps and Flow

1. Experiment Environment Setup

• Install the operating system and configure the development environment.
• Write a process scheduling simulation program, including process creation, state management, and scheduling logic.

2. Scheduling Algorithm Implementation

• FCFS Implementation: Maintain a queue based on arrival order and sequentially schedule processes.
• SJF Implementation: Sort processes by estimated execution time and prioritize short jobs.
• Priority Implementation: Assign priority values to processes and schedule them based on priority.
• RR Implementation: Set time slice parameters and allocate CPU in a round-robin manner.

3. Test Case Design

• Baseline Test: Run 10 processes with the same priority to observe scheduling results.
• Performance Comparison: Compare average waiting time and throughput under different algorithms.
• Abnormal Scenarios: Simulate high-priority process preempting low-priority processes.

4. Data Recording and Analysis

• Record execution order, waiting time, and CPU utilization for each scheduling algorithm.
• Use charts (e.g., bar graphs, line graphs) to compare performance differences among algorithms.

Experimental Data Analysis and Results

Key Metrics Comparison

Typical Scenario Analysis

• Shortest Job First (SJF): Significantly reduces average waiting time when there are many short jobs in the task set.
• Round-Robin (RR): Avoids long CPU occupation by multiple processes, improving system responsiveness.
• Priority Scheduling: High-priority processes can timely respond in real-time systems, but may cause low-priority processes to starve.

Experimental Conclusion and Reflections

Experimental Conclusion

1. The selection of scheduling algorithms requires a balance between performance and fairness: SJF excels in reducing waiting time but may sacrifice fairness; RR provides better fairness but may lower throughput.
2. Priority scheduling implementations must avoid priority inversion: Solve this through priority preemption mechanisms or priority preemption priority (e.g., priority preemption priority).
3. System performance is directly influenced by scheduling strategies: Rational selection of scheduling algorithms can significantly improve system efficiency.

Further Research Directions

• Hybrid Scheduling Algorithms: Combine multiple scheduling strategies (e.g., SJF + Priority) for optimized performance.
• Dynamic Priority Adjustment: Dynamically adjust priorities based on process runtime states to prevent starvation.
• Multi-Core Environment Optimization: Explore parallel scheduling methods for multi-threaded or multi-process scenarios.

Experimental Notes and Recommendations

• Avoid Deadlocks: Ensure no circular resource waiting in scheduling logic.
• Comprehensive Test Cases: Cover normal operations, abnormal terminations, and resource competition scenarios.
• Performance Monitoring Tools: Use top, htop, or perf to monitor resource usage in real time.
• Code Debugging Techniques: Use GDB to step through process scheduling logic and verify state transitions.