Slack time
This scheduling algorithm first selects those processes that have the smallest "slack time". Slack time is defined as the temporal difference between the deadline, the ready time and the run time.
More formally, the slack time
for a process is defined as:
where 
is the process deadline, 
is the real time since the cycle start, and 
is the remaining computation time.
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.
Queueing theory is the mathematical study of waiting lines, or queues. A queueing model is constructed so that queue lengths and waiting time can be predicted. Queueing theory is generally considered a branch of operations research because the results are often used when making business decisions about the resources needed to provide a service.
Simulated annealing (SA) is a probabilistic technique for approximating the global optimum of a given function. Specifically, it is a metaheuristic to approximate global optimization in a large search space for an optimization problem. For large numbers of local optima, SA can find the global optima. It is often used when the search space is discrete. For problems where finding an approximate global optimum is more important than finding a precise local optimum in a fixed amount of time, simulated annealing may be preferable to exact algorithms such as gradient descent or branch and bound.
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.
Nonlinear dimensionality reduction, also known as manifold learning, refers to various related techniques that aim to project high-dimensional data onto lower-dimensional latent manifolds, with the goal of either visualizing the data in the low-dimensional space, or learning the mapping itself. The techniques described below can be understood as generalizations of linear decomposition methods used for dimensionality reduction, such as singular value decomposition and principal component analysis.
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.
Single-machine scheduling or single-resource scheduling is an optimization problem in computer science and operations research. We are given n jobs J1, J2, ..., Jn of varying processing times, which need to be scheduled on a single machine, in a way that optimizes a certain objective, such as the throughput.
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.
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.
Real-time database has two meanings. The most common use of the term refers to a database system which uses streaming technologies to handle workloads whose state is constantly changing. This differs from traditional databases containing persistent data, mostly unaffected by time. When referring to streaming technologies, real-time processing means that a transaction is processed fast enough for the result to come back and be acted on right away. Such real-time databases are useful for assisting social media platforms in the removal of fake news, in-store surveillance cameras identifying potential shoplifters by their behavior/movements, etc.
In computing, computer performance is the amount of useful work accomplished by a computer system. Outside of specific contexts, computer performance is estimated in terms of accuracy, efficiency and speed of executing computer program instructions. When it comes to high computer performance, one or more of the following factors might be involved:
The Stack Resource Policy (SRP) is a resource allocation policy used in real-time computing, used for accessing shared resources when using earliest deadline first scheduling. It was defined by T. P. Baker. SRP is not the same as the Priority ceiling protocol which is for fixed priority tasks (FP).
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.
Heterogeneous earliest finish time is a heuristic to schedule a set of dependent tasks onto a network of heterogenous workers taking communication time into account. For inputs HEFT takes a set of tasks, represented as a directed acyclic graph, a set of workers, the times to execute each task on each worker, and the times to communicate the results from each job to each of its children between each pair of workers. It descends from list scheduling algorithms.
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.
YDS is a scheduling algorithm for dynamic speed scaling processors which minimizes the total energy consumption. It was named after and developed by Yao et al. There is both an online and an offline version of the algorithm.
This is a list of the individual topics in Electronics, Mathematics, and Integrated Circuits that together make up the Computer Engineering field. The organization is by topic to create an effective Study Guide for this field. The contents match the full body of topics and detail information expected of a person identifying themselves as a Computer Engineering expert as laid out by the National Council of Examiners for Engineering and Surveying. It is a comprehensive list and superset of the computer engineering topics generally dealt with at any one time.
