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A queue or queueing node can be thought of as nearly a black box. Jobs (also called customers or requests, depending on the field) arrive to the queue, possibly wait some time, take some time being processed, and then depart from the queue. A black box. Jobs arrive to, and depart from, the queue.
Queues provide services in computer science, transport, and operations research where various entities such as data, objects, persons, or events are stored and held to be processed later. In these contexts, the queue performs the function of a buffer. Another usage of queues is in the implementation of breadth-first search.
A network of m interconnected queues is known as a Jackson network [11] or Jacksonian network [12] if it meets the following conditions: if the network is open, any external arrivals to node i form a Poisson process, All service times are exponentially distributed and the service discipline at all queues is first-come, first-served,
It has since been extended to A/S/c/K/N/D where K is the capacity of the queue, N is the size of the population of jobs to be served, and D is the queueing discipline. [ 2 ] [ 3 ] [ 4 ] When the final three parameters are not specified (e.g. M/M/1 queue ), it is assumed K = ∞, N = ∞ and D = FIFO .
Fair queuing uses one queue per packet flow and services them in rotation, such that each flow can "obtain an equal fraction of the resources". [1] [2]The advantage over conventional first in first out (FIFO) or priority queuing is that a high-data-rate flow, consisting of large packets or many data packets, cannot take more than its fair share of the link capacity.
Many implementations of message queues function internally within an operating system or within an application. Such queues exist for the purposes of that system only. [3] [4] [5] Other implementations allow the passing of messages between different computer systems, potentially connecting multiple applications and multiple operating systems. [6]
An M/M/∞ queue is a stochastic process whose state space is the set {0,1,2,3,...} where the value corresponds to the number of customers currently being served. Since, the number of servers in parallel is infinite, there is no queue and the number of customers in the systems coincides with the number of customers being served at any moment.
Service times have an exponential distribution with rate parameter μ in the M/M/1 queue, where 1/μ is the mean service time. All arrival times and services times are (usually) assumed to be independent of one another. [2] A single server serves customers one at a time from the front of the queue, according to a first-come, first-served ...