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In computing, a context switch is the process of storing the state of a process or thread, so that it can be restored and resume execution at a later point, and then restoring a different, previously saved, state. This allows multiple processes to share a single central processing unit (CPU), and is an essential feature of a multiprogramming or multitasking operating system. In a traditional CPU, each process - a program in execution - utilizes the various CPU registers to store data and hold the current state of the running process. However, in a multitasking operating system, the operating system switches between processes or threads to allow the execution of multiple processes simultaneously. For every switch, the operating system must save the state of the currently running process, followed by loading the next process state, which will run on the CPU. This sequence of operations that stores the state of the running process and the loading of the following running process is called a context switch.
Real-time computing (RTC) is the computer science term for hardware and software systems subject to a "real-time constraint", for example from event to system response. Real-time programs must guarantee response within specified time constraints, often referred to as "deadlines".
A real-time operating system (RTOS) is an operating system (OS) for real-time computing applications that processes data and events that have critically defined time constraints. An RTOS is distinct from a time-sharing operating system, such as Unix, which manages the sharing of system resources with a scheduler, data buffers, or fixed task prioritization in a multitasking or multiprogramming environment. Processing time requirements need to be fully understood and bound rather than just kept as a minimum. All processing must occur within the defined constraints. Real-time operating systems are event-driven and preemptive, meaning the OS can monitor the relevant priority of competing tasks, and make changes to the task priority. Event-driven systems switch between tasks based on their priorities, while time-sharing systems switch the task based on clock interrupts.
In computing, load balancing is the process of distributing a set of tasks over a set of resources, with the aim of making their overall processing more efficient. Load balancing can optimize the response time and avoid unevenly overloading some compute nodes while other compute nodes are left idle.
In computing, scheduling is the action of assigning resources to perform tasks. The resources may be processors, network links or expansion cards. The tasks may be threads, processes or data flows.
In computer science, rate-monotonic scheduling (RMS) is a priority assignment algorithm used in real-time operating systems (RTOS) with a static-priority scheduling class. The static priorities are assigned according to the cycle duration of the job, so a shorter cycle duration results in a higher job priority.
In computer science, priority inversion is a scenario in scheduling in which a high priority task is indirectly superseded by a lower priority task effectively inverting the assigned priorities of the tasks. This violates the priority model that high-priority tasks can only be prevented from running by higher-priority tasks. Inversion occurs when there is a resource contention with a low-priority task that is then preempted by a medium-priority task.
In computer systems programming, an interrupt handler, also known as an interrupt service routine or ISR, is a special block of code associated with a specific interrupt condition. Interrupt handlers are initiated by hardware interrupts, software interrupt instructions, or software exceptions, and are used for implementing device drivers or transitions between protected modes of operation, such as system calls.
Least slack time (LST) scheduling is an algorithm for dynamic priority scheduling. It assigns priorities to processes based on their slack time. Slack time is the amount of time left after a job if the job was started now. This algorithm is also known as least laxity first. Its most common use is in embedded systems, especially those with multiple processors. It imposes the simple constraint that each process on each available processor possesses the same run time, and that individual processes do not have an affinity to a certain processor. This is what lends it a suitability to embedded systems.
In computer science, gang scheduling is a scheduling algorithm for parallel systems that schedules related threads or processes to run simultaneously on different processors. Usually these will be threads all belonging to the same process, but they may also be from different processes, where the processes could have a producer-consumer relationship or come from the same MPI program.
Optimal job scheduling is a class of optimization problems related to scheduling. The inputs to such problems are a list of jobs and a list of machines. The required output is a schedule – an assignment of jobs to machines. The schedule should optimize a certain objective function. In the literature, problems of optimal job scheduling are often called machine scheduling, processor scheduling, multiprocessor scheduling, or just scheduling.
Interval scheduling is a class of problems in computer science, particularly in the area of algorithm design. The problems consider a set of tasks. Each task is represented by an interval describing the time in which it needs to be processed by some machine. For instance, task A might run from 2:00 to 5:00, task B might run from 4:00 to 10:00 and task C might run from 9:00 to 11:00. A subset of intervals is compatible if no two intervals overlap on the machine/resource. For example, the subset {A,C} is compatible, as is the subset {B}; but neither {A,B} nor {B,C} are compatible subsets, because the corresponding intervals within each subset overlap.
Dynamic priority scheduling is a type of scheduling algorithm in which the priorities are calculated during the execution of the system. The goal of dynamic priority scheduling is to adapt to dynamically changing progress and to form an optimal configuration in a self-sustained manner. It can be very hard to produce well-defined policies to achieve the goal depending on the difficulty of a given problem.
Multi-level queueing, used at least since the late 1950s/early 1960s, is a queue with a predefined number of levels. Items get assigned to a particular level at insert, and thus cannot be moved to another level. Items get removed from the queue by removing all items from a level, and then moving to the next. If an item is added to a level above, the "fetching" restarts from there. Each level of the queue is free to use its own scheduling, thus adding greater flexibility than merely having multiple levels in a queue.
In computing, job control refers to the control of multiple tasks or jobs on a computer system, ensuring that they each have access to adequate resources to perform correctly, that competition for limited resources does not cause a deadlock where two or more jobs are unable to complete, resolving such situations where they do occur, and terminating jobs that, for any reason, are not performing as expected.
In computer science for Operating systems, aging or ageing is a scheduling technique used to avoid starvation. Fixed priority scheduling is a scheduling discipline, in which tasks queued for utilizing a system resource are assigned a priority each. A task with a high priority is allowed to access a specific system resource before a task with a lower priority is allowed to do the same. A disadvantage of this approach is that tasks assigned with a lower priority may be starved when a large number of high priority tasks are queued. Aging is used to gradually increase the priority of a task, based on its waiting time in the ready queue.
The Brain Fuck Scheduler (BFS) is a process scheduler designed for the Linux kernel in August 2009 as an alternative to the Completely Fair Scheduler (CFS) and the O(1) scheduler. BFS was created by an experienced kernel programmer Con Kolivas.
SCHED_DEADLINE is a CPU scheduler available in the Linux kernel since version 3.14, based on the Earliest Deadline First (EDF) and Constant Bandwidth Server (CBS) algorithms, supporting resource reservations: each task scheduled under such policy is associated with a budget Q, and a period P, corresponding to a declaration to the kernel that Q time units are required by that task every P time units, on any processor. This makes SCHED_DEADLINE particularly suitable for real-time applications, like multimedia or industrial control, where P corresponds to the minimum time elapsing between subsequent activations of the task, and Q corresponds to the worst-case execution time needed by each activation of the task.
Earliest deadline first (EDF) or least time to go is a dynamic priority scheduling algorithm used in real-time operating systems to place processes in a priority queue. Whenever a scheduling event occurs the queue will be searched for the process closest to its deadline. This process is the next to be scheduled for execution.
The term scheduling analysis in real-time computing includes the analysis and testing of the scheduler system and the algorithms used in real-time applications. In computer science, real-time scheduling analysis is the evaluation, testing and verification of the scheduling system and the algorithms used in real-time operations. For critical operations, a real-time system must be tested and verified for performance.
References
- ↑ "Deadline Monotonic Scheduling". 1990. CiteSeerX 10.1.1.53.8928 .
- ↑ Alan Burns and Andy Wellings (2001). Real-Time Systems and Programming Languages (3rd ed.). Addison Wesley. p. 485. ISBN 0-201-72988-1.
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