Queueing models with constricting waiting time and energy consumption in a base station using threshold policy

Abstract

newlineWaiting is an unpleasant task in today s fast-paced society, yet it is newlineunavoidable when resources are limited. The goal of service providers is to give newlineservice to everyone in a reasonable amount of time. This might be impossible newlinedue to a number of causes such as traffic, server failure, server vacation, and so newlineon. It is critical to assess such systems before deploying them in order to meet newlinethe goals of service providers. This is achievable using queueing theory. newlineSome real-world queueing models are theoretically developed in newlinethis work, with additional features such as disaster, working breakdown, newlinestate dependent arrival, optional re-service, working vacation, restricted newlineadmissibility, flexible batch service, multiple sleeps with N-policy, close down, newlinesetup, and finite buffer. To derive the probability generating function of all newlinemodels, the supplementary variable technique was used. Measures such as the newlinesteady-state probability of different server states, the mean customer waiting newlinetime, the mean number of customers in the system, and so on were determined newlineusing analytical, simulation, or both analytical and simulation methodologies. newlineFinally, the findings were numerically confirmed. newline