scheduler

A scheduler is a software component that decides which task should run at any given time and how system resources such as CPU time, memory, or network bandwidth are allocated. In computing, schedulers are central to operating systems, real-time platforms, distributed systems, and application frameworks, guiding execution order, timing, and resource usage while aiming to balance efficiency and fairness.

In operating systems, CPU scheduling selects the next process or thread to run. Schedulers may be preemptive or non-preemptive. Classic policies include first-come-first-served, shortest job first, priority scheduling, round-robin, and multilevel feedback queues. Real-time systems distinguish hard and soft deadlines and use methods such as rate-monotonic or earliest-deadline-first. Modern systems also employ complex strategies; examples include Linux's Completely Fair Scheduler and Windows' priority-based preemptive scheduler. In cloud environments, Kubernetes assigns pods to nodes based on resource requests and constraints.

In batch and distributed computing, schedulers manage tasks across clusters, handle dependencies, retries, and service-level agreements. Notable systems include Slurm, Apache Hadoop YARN, HTCondor, and workflow schedulers like Apache Airflow. Application frameworks often integrate schedulers to trigger tasks at specific times or in response to events.

Scheduling theory studies mathematical models for sequencing and timing, addressing problems such as job shop and flow shop, with objectives like minimizing makespan, lateness, or cost. It provides algorithms and performance guarantees for various practical domains.

Key design concerns include fairness, predictability, efficiency, and minimizing scheduling overhead, especially under bursty workloads or real-time constraints.