Abstract: In heterogeneous distributed computing platforms, task execution containers (e.g., Spark executors) often exhibit significant performance variations. However, most task schedulers greedily ...
Abstract: Task scheduling is a classical problem in AI-driven optimization, traditionally tackled using machine learning or heuristic search algorithms. However, most existing methods primarily focus ...