Scheduling Algorithm

Scheduling algorithms optimize the allocation of resources to tasks, aiming to minimize completion times, costs, or maximize other objectives like net present value or resource utilization. Current research focuses on improving efficiency in diverse contexts, including large language models (using embedding-based predictions and limited preemption), cloud computing (employing metaheuristics like modified Salp Swarm Algorithms), and federated learning (minimizing energy consumption). These advancements are crucial for improving the performance and resource efficiency of various systems, from high-performance computing to resource-constrained mobile environments.