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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. [1] SRP is not the same as the Priority ceiling protocol which is for fixed priority tasks (FP).
Each task is assigned a preemption level based upon the following formula where denotes the deadline of task and denotes the preemption level of task i:
Each resource R has a current ceiling that represents the maximum of the preemption levels of the tasks that may be blocked, when there are units of available and is the maximum units of that may require at any one time. is assigned as follows:
There is also a system ceiling which is the maximum of all current ceilings of the resources.
Any task that wishes to preempt the system must first satisfy the following constraint:
This can be refined for Operating System implementation (as in MarteOS) by removing the multi-unit resources and defining the stack resource policy as follows
The 2011 book Hard Real-Time Computing Systems: Predictable Scheduling Algorithms and Applications by Giorgio C. Buttazzo featured a dedicated section to reviewing SRP from Baker 1991 work. [2] [3]
The Cauchy distribution, named after Augustin Cauchy, is a continuous probability distribution. It is also known, especially among physicists, as the Lorentz distribution, Cauchy–Lorentz distribution, Lorentz(ian) function, or Breit–Wigner distribution. The Cauchy distribution is the distribution of the x-intercept of a ray issuing from with a uniformly distributed angle. It is also the distribution of the ratio of two independent normally distributed random variables with mean zero.
Reinforcement learning (RL) is an area of machine learning concerned with how intelligent agents ought to take actions in an environment in order to maximize the notion of cumulative reward. Reinforcement learning is one of three basic machine learning paradigms, alongside supervised learning and unsupervised learning.
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 probability theory and statistics, the Gumbel distribution is used to model the distribution of the maximum of a number of samples of various distributions.
In radio and telecommunications a dipole antenna or doublet is the simplest and most widely used class of antenna. The dipole is any one of a class of antennas producing a radiation pattern approximating that of an elementary electric dipole with a radiating structure supporting a line current so energized that the current has only one node at each end. A dipole antenna commonly consists of two identical conductive elements such as metal wires or rods. The driving current from the transmitter is applied, or for receiving antennas the output signal to the receiver is taken, between the two halves of the antenna. Each side of the feedline to the transmitter or receiver is connected to one of the conductors. This contrasts with a monopole antenna, which consists of a single rod or conductor with one side of the feedline connected to it, and the other side connected to some type of ground. A common example of a dipole is the "rabbit ears" television antenna found on broadcast television sets.
In computational complexity theory, a complexity class is a set of computational problems of related resource-based complexity. The two most commonly analyzed resources are time and memory.
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.
The Gaussian integral, also known as the Euler–Poisson integral, is the integral of the Gaussian function over the entire real line. Named after the German mathematician Carl Friedrich Gauss, the integral is
In physics, the reciprocal lattice represents the Fourier transform of another lattice (group). In normal usage, the initial lattice is a periodic spatial function in real space known as the direct lattice. While the direct lattice exists in real space and is commonly understood to be a physical lattice, the reciprocal lattice exists in the space of spatial frequencies known as reciprocal space or k space, where refers to the wavevector. In quantum physics, reciprocal space is closely related to momentum space according to the proportionality , where is the momentum vector and is the Planck constant. The reciprocal lattice of a reciprocal lattice is equivalent to the original direct lattice, because the defining equations are symmetrical with respect to the vectors in real and reciprocal space. Mathematically, direct and reciprocal lattice vectors represent covariant and contravariant vectors, respectively.
In telecommunications, particularly in radio frequency engineering, signal strength refers to the transmitter power output as received by a reference antenna at a distance from the transmitting antenna. High-powered transmissions, such as those used in broadcasting, are expressed in dB-millivolts per metre (dBmV/m). For very low-power systems, such as mobile phones, signal strength is usually expressed in dB-microvolts per metre (dBμV/m) or in decibels above a reference level of one milliwatt (dBm). In broadcasting terminology, 1 mV/m is 1000 μV/m or 60 dBμ.
In electrical engineering, statistical computing and bioinformatics, the Baum–Welch algorithm is a special case of the expectation–maximization algorithm used to find the unknown parameters of a hidden Markov model (HMM). It makes use of the forward-backward algorithm to compute the statistics for the expectation step.
Critical point is a wide term used in many branches of mathematics.
In mathematics, sine and cosine are trigonometric functions of an angle. The sine and cosine of an acute angle are defined in the context of a right triangle: for the specified angle, its sine is the ratio of the length of the side that is opposite that angle to the length of the longest side of the triangle, and the cosine is the ratio of the length of the adjacent leg to that of the hypotenuse. For an angle , the sine and cosine functions are denoted simply as and .
Task systems are mathematical objects used to model the set of possible configuration of online algorithms. They were introduced by Borodin, Linial and Saks (1992) to model a variety of online problems. A task system determines a set of states and costs to change states. Task systems obtain as input a sequence of requests such that each request assigns processing times to the states. The objective of an online algorithm for task systems is to create a schedule that minimizes the overall cost incurred due to processing the tasks with respect to the states and due to the cost to change states.
In computer science and discrete mathematics, an inversion in a sequence is a pair of elements that are out of their natural order.
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.
Oliver E. Williamson hypothesised (1964) that profit maximization would not be the objective of the managers of a joint stock organisation. This theory, like other managerial theories of the firm, assumes that utility maximisation is a manager’s sole objective. However it is only in a corporate form of business organisation that a self-interest seeking manager maximise his/her own utility, since there exists a separation of ownership and control. The managers can use their ‘discretion’ to frame and execute policies which would maximise their own utilities rather than maximising the shareholders’ utilities. This is essentially the principal–agent problem. This could however threaten their job security, if a minimum level of profit is not attained by the firm to distribute among the shareholders.
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 problem of Multi-Agent Path Finding (MAPF) is an instance of multi-agent planning and consists in the computation of collision-free paths for a group of agents from their location to an assigned target. It is an optimization problem, since the aim is to find those paths that optimize a given objective function, usually defined as the number of time steps until all agents reach their goal cells. MAPF is the multi-agent generalization of the pathfinding problem, and it is closely related to the shortest path problem in the context of graph theory.
