Scheduling (computing)

In computing, scheduling refers to the method by which tasks are assigned to resources, particularly in the context of operating systems and process management. The goal of scheduling is to efficiently manage the execution of multiple processes or threads on a computer system, optimizing resource utilization, responsiveness, and overall performance. ### Types of Scheduling 1. **Long-term Scheduling**: Determines which processes are admitted to the system for processing. It controls the degree of multiprogramming (the number of processes in memory).

I/O scheduling refers to the method by which an operating system determines the order in which I/O operations are processed. It involves managing the access to input/output devices—such as hard drives, network interfaces, and other peripherals—to optimize system performance, resource utilization, and responsiveness. Key objectives of I/O scheduling include: 1. **Maximizing Throughput**: Ensuring the highest number of I/O operations are completed in a given time frame.

Job scheduling is the process of planning and executing tasks or jobs in a computing environment, particularly in operating systems and data processing systems. It involves determining the order and timing in which jobs will be executed based on various criteria, such as resource availability, job priority, and specific timing requirements. Job scheduling can apply to a variety of contexts, including: 1. **Operating Systems**: In a multitasking operating system, the job scheduler is responsible for allocating CPU time to various processes.

In computing, "blocking" refers to a situation where a process or thread is unable to continue execution until a certain condition is met or a resource becomes available. This often occurs in contexts such as I/O operations, synchronization, and resource management.

"Idle" in the context of CPU usage refers to the state when the CPU is not actively processing any tasks. This means that the CPU is waiting for instructions, or it is handling minimal background processes, resulting in low or no workload. When a CPU is in an idle state, it is not consuming significant resources, and the percentage of CPU utilization will be low (often shown as a percentage in system monitoring tools).

Kernel preemption is a feature of operating systems, particularly within the context of the Linux kernel, that allows a running process to be interrupted so that the operating system can switch to another process. This mechanism is crucial for allowing a responsive multitasking environment, enabling the system to handle various processes efficiently. In preemptive multitasking systems, the kernel can suspend the execution of a process to allocate CPU time to another process that is ready to run.

A lightweight process (LWP) is a type of process in operating systems that shares the same address space but operates independently, allowing for concurrent execution. Lightweight processes are often associated with threads, which are the smallest unit of processing that can be scheduled by an operating system. Here are some key characteristics of lightweight processes: 1. **Shared Resources**: LWPs share the same memory space and other resources (like file descriptors) with other threads in the same process.

Makespan is a term used in project management, operations research, and scheduling that refers to the total time required to complete a set of tasks or jobs from start to finish. Specifically, it is defined as the time at which the last job is completed. In other words, makespan measures the overall duration of a project or process, helping to evaluate its efficiency.

Resource allocation in computer systems refers to the process of distributing available resources—such as CPU time, memory, disk space, and network bandwidth—among various tasks, applications, or users in an efficient manner. This is a critical aspect of operating systems and computer architecture, as it directly impacts system performance, responsiveness, and overall efficiency. ### Key Aspects of Resource Allocation: 1. **Types of Resources**: - **CPU Time**: Allocation of processing power to different tasks.

In computing, particularly in operating system terminology, a **run queue** (or **ready queue**) refers to a data structure used by the operating system's scheduler to keep track of processes that are in a runnable state, meaning they are ready to execute but are not currently running on a CPU. Here are some key points regarding the run queue: 1. **State of Processes**: Processes in the run queue are generally in the "ready" state.

A schedule is a plan or timetable that outlines when specific events, tasks, or activities will occur. It serves as a guide to help organize time effectively. Schedules can vary widely in complexity and purpose, including: 1. **Daily Schedule:** Typically includes appointments, tasks, and activities planned for a single day. It helps individuals manage their time effectively. 2. **Weekly/Monthly Schedule:** This type of schedule outlines tasks and commitments over a longer period, allowing for better planning and prioritization.

Scheduling analysis in real-time systems is a crucial aspect of ensuring that tasks in such systems meet their timing constraints. Real-time systems are systems in which the correctness of the operation depends not only on the logical result of computations but also on the time at which the results are produced. This makes scheduling — the decision of when and how tasks are executed — a fundamental concern.

The term "server hog" generally refers to a software application or process that consumes an excessive amount of server resources, such as CPU, memory, or bandwidth, resulting in degraded performance for other applications or users on the same server. This can lead to slow response times, increased latency, or even crashes if the server becomes overwhelmed by the resource demands of the hogging application.

Stochastic scheduling is a concept in operations research and computer science that deals with scheduling problems in environments where there is uncertainty or randomness in the durations of tasks, arrival times, or other parameters. Unlike deterministic scheduling, where all parameters are known with certainty, stochastic scheduling incorporates variability and probabilistic models to make decisions that optimize certain performance measures, such as minimizing completion time, maximizing resource utilization, or achieving deadlines.

Tardiness in scheduling refers to the amount of time a task or job is completed later than its scheduled or planned time. It is a critical performance metric in various fields, including project management, manufacturing, and operations management, where timing is essential for efficiency and productivity. Tardiness can be influenced by numerous factors, including delays in task execution, resource availability, unexpected disruptions, and poor planning. In scheduling contexts, it can refer to individual tasks or an entire project.