# Least Slack Time (LST) scheduling Algorithm in real-time systems

The Least Slack Time (LST) scheduling algorithm is a real-time scheduling algorithm that prioritizes tasks based on the amount of time remaining before a task's deadline. The LST algorithm's basic idea is to schedule the task with the least slack time first because it has the least amount of time before its deadline.

Real-time systems are intended to handle tasks or jobs with strict time constraints. These tasks are frequently carried out in a periodic or ad hoc fashion, with each task having a specific deadline by which it must be completed. Real-time scheduling algorithms aid in the completion of these tasks on time.

The LS,T scheduling algorithm is a real-time scheduling algorithm that prioritizes tasks based on how much time they have between them. Slack time is the amount of time left before a task's deadline after accounting for time already spent on the task. A task with a large slack time has more time to complete it before the deadline, whereas a task with a small slack time has less time before the deadline.

The LST scheduling algorithm operates in the following manner −

• Calculate the slack time for each task − The LST scheduling algorithm's first step is to calculate the slack time for each task. The difference between the task's deadline and its execution time is used to calculate slack time. For instance, if a task has a deadline of 10 seconds and has already been running for 3 seconds, its slack time is 7 seconds.

• Sorting the tasks according to their slack time in ascending order − The algorithm sorts the tasks in ascending order after calculating the slack time for each task. The algorithm bases the sorting on their slack time and prioritizes task with the least amount of slack time.

• Schedule the task with the least amount of slack time first − This step is to schedule the task with the least amount of slack time first. Here, the task with the least amount of time until its deadline is first completed. As soon as the task is completed, the slack time for the remaining tasks is recalculated. The tasks are then in turn, sorted based on their recalculated slack times.

• Steps 1–3 should be repeated until all tasks are scheduled

• The LST scheduling algorithm has the advantage of being able to handle both periodic and aperiodic tasks. Aperiodic tasks occur at irregular intervals, whereas periodic tasks occur at regular intervals. Regardless of whether the tasks are periodic or aperiodic, the LST scheduling algorithm can prioritize them based on their slack time.

• Another benefit of the LST scheduling algorithm is that it strikes a good balance between meeting deadlines and efficiently utilizing system resources. The algorithm ensures that tasks are completed on time by scheduling them with the least amount of slack time first. Simultaneously, by prioritizing tasks based on their slack time, the algorithm ensures that system resources are used efficiently.

## Limitations

• The LST algorithm prioritizes tasks based on their slack time, which is the time remaining before a task's deadline. It is not suitable for hard real-time systems. In hard real-time systems, however, missing a deadline can have serious consequences, so strict deadlines must be met. As a result, LST may not be appropriate for such systems.

• Sorting overhead − The LST algorithm necessitates sorting the task list based on slack time, which can be computationally expensive, especially in large-task systems.

• Difficulty in dealing with sporadic tasks − The LST algorithm is intended to handle both periodic and aperiodic tasks. However, it may be incapable of handling sporadic tasks efficiently, which occur at random and may have varying execution times.

• Potential for priority inversion − If a high-priority task is waiting for a low-priority task with less slack time, a priority inversion can occur. Priority inversion occurs when a lower-priority task holds a resource needed by a higher-priority task, preventing it from executing and potentially causing deadlines to be missed.

• Preemption overhead − Because the LST algorithm supports preemption, a task with a shorter slack time can preempt a task with a longer slack time. However, frequent preemptions can increase overhead and have an impact on the system.