LEARNING JOURNAL

I created this learning journal to practice writting and to help me learn by writting everything down. Source code here

2/28/2024

Task Scheduler

THE PROBLEM

After solving Leetcode problems for awhile, I realize that everything is boiled down to knowing what data structure and algorithm to use and how to use them effectively. So first, you need to understand your "tools" (algorithms and data structures) really well. For example, this problem.

Because after each task, there is a certain amount of resting interval. So, the worse case scenario is that the tasks that appear most frequent are the only ones that left. So, you need to complete them and do nothing after n cycles, which cost time. So, the trick is to do the tasks that has the highest frequency first. It's a call for max heap.

So basically, you can organize the running time into many round, each round will take n + 1 cycles (with n is the constraint of resting cycles after each task). The idea is that you have to execute the task that happens that most right when it is available (which is the next round), otherwise, you fill up the round with the less frequent tasks.

Revised by ChatGPT

The "Task Scheduler" problem requires scheduling a list of tasks with cooling intervals between the same tasks. The goal is to find the minimum total time needed to complete all tasks.

Approach:

The key insight is that tasks with the highest frequency should be scheduled first to minimize idle time. This is because the worst-case scenario is having to wait for the cooling interval after completing all instances of the most frequent task. To implement this, we use a max heap to prioritize tasks based on their frequency.

We organize the scheduling into rounds, each round lasting n + 1 cycles, where n is the cooling interval. In each round, we execute the most frequent task available and fill the remaining slots with less frequent tasks. This ensures that we minimize idle time by keeping the processor busy with other tasks while waiting for the cooling interval of the most frequent tasks to pass.

Example:

Consider tasks A, A, A, B, B, C with a cooling interval of 2. We can schedule them as follows: Round 1: A B C Round 2: A B _ Round 3: A _ _

The total time taken is 8 cycles.

By understanding our "tools" (algorithms and data structures) and applying them effectively, we can solve complex problems like this one efficiently.