- QUEUEING THEORY
Waiting time is never a preferable option for any of us. In order to diminish that disgust cost is to be incurred. For both the reduction and avoidance of such time costs investments. When deciding that wither we should invest or not the cost in terms of waiting time is compared with the cost that is incurred to reduce the waiting time. The cost that is overall lower is usually opted and is considered as an alternative that can be worked upon. For the purpose of this comparison some techniques and models are used. These models and techniques are usually used in terms of calculating the costs of waiting time. One of the best model that stands at the top of the list is the queuing model (Willig, 1999).
Queuing is primarily considered an extension of Applied Probability theory. It has range of applications and it used in different realms, such as communication, networks, computer systems, machine plants, supermarkets and call centers.
Queuing theory can be explained or elaborated as follows. Think of a service center and the populace, which visits Service Center, frequently, to acquire services. Because of the operational capacity, Service Center can only serve a certain numbers, from the populace. When a Service Center is burdened, a fresh client has to wait, until system becomes operational or available again. This helps us acknowledge three elements or aspects of service center; 1) Population, 2) Service facility and 3) Waiting line. Queuing theory helps in forming network of Service Centers, which can avoid waiting lines and can keep Service center operational for clients, from a certain population.
An airline counter could be an opposite example for a Service Center, where travelers are presumed to check in. Most of the time, check-in services are provided by a single employee. In case there are number of travelers and only a single employee to provide services, passenger or traveler has to wait in the queue. This is referred as FIFO service, First In, First Out.
Examples, pertaining to Queuing theory, from the realm of Network are the buffers in Dimensioning of routers, computing and the determination of the trunks’ digits, in the Head Quarters, which is located in POTS, Comprehensive or end achievingcomputation, from network systems.
Queuing theory addresses or answers questions, such as the mean time client splurges waiting in the queue, the mean time system takes to respond, mean consumption of a service feature or facility, mean distribution of clients (in a queue), mean distributing pertaining to clients. These core questions are scrutinized in stochastic situation, in which client arrival and response system, of Service Center are taken randomly.
A client comes to a Service Center, in a random manner. There can be one or more than one servers, provided by Service facility, with the capacity or ability to serve only a single client or customer at a given time. The required time, to provide services to a customer, are also assumed or modeled random. Following figure shows an example of that kind of queue.An example is shown in the following figure of that kind of queue.