Queue occupancy and server size distribution of a queue length dependent vacation queue with an optional service

TL;DR

This paper models a discrete-time queue with batch arrivals, vacations, and two-phase service, providing detailed joint distributions and sensitivity analysis relevant to modern telecommunication systems like 5G and IoT.

Contribution

It introduces a comprehensive analytical framework for a queue with batch arrivals, vacations, and two-phase service, including joint distributions and numerical illustrations.

Findings

Derived joint probability generating functions for queue states

Established complete joint distribution at arbitrary times

Performed sensitivity analysis on key system parameters

Abstract

The discrete time queueing system is highly applicable to modern telecommunication systems, where it provides adaptive packet handling, congestion controlled security/inspection, energy efficient operation, and supports bursty traffic common in 5G, Internet of Things (IoT), and edge computing environments. In this article, we analyze an infinite-buffer discrete-time batch-arrival queue with single and multiple vacation policy where customers are served in batches, in two phases, namely first essential service (FES) and second optional service (SOS). In such systems, the FES corresponds to basic data processing or packet routing, while SOS represents secondary tasks such as encryption, error checking, data compression, or deep packet inspection that may not be necessary for every packet. Here, we derive the bivariate probability generating functions for the joint distribution of the number of packets waiting for transmission and the number are being processed immediately after the completion of both the FES and SOS. Furthermore, the complete joint distribution at arbitrary time slots, including vacation completion states, is established. Numerical illustrations demonstrate the applicability of the proposed framework, including an example with discrete phase type service time distribution. Finally, the sensitivity analysis of the key parameters on marginal system's probabilities and different performance measures have been investigated through several graphical representations.