Delay analysis of a two-class batch-service queue with class-dependent variable server capacity

In this paper, we analyse the delay of a random customer in a two-class batch-service queueing model with variable server capacity, where all customers are accommodated in a common single-server first-come-first-served queue. The server can only process customers that belong to the same class, so that the size of a batch is determined by the length of a sequence of same-class customers. This type of batch server can be found in telecommunications systems and production environments. We first determine the steady state partial probability generating function of the queue occupancy at customer arrival epochs. Using a spectral decomposition technique, we obtain the steady state probability generating function of the delay of a random customer. We also show that the distribution of the delay of a random customer corresponds to a phase-type distribution. Finally, some numerical examples are given that provide further insight in the impact of asymmetry and variance in the arrival process on the number of customers in the system and the delay of a random customer

Analysis of a batch-service queue with variable service capacity, correlated customer types and generally distributed class-dependent service times

Queueing models with batch service have been studied frequently, for instance in the domain of telecommunications or manufacturing. Although the batch server's capacity may be variable in practice, only a few authors have included variable capacity in their models. We analyse a batch server with multiple customer classes and a variable service capacity that depends on both the number of waiting customers and their classes. The service times are generally distributed and class-dependent. These features complicate the analysis in a non-trivial way. We tackle it by examining the system state at embedded points, and studying the resulting Markov Chain. We first establish the joint probability generating function (pgf) of the service capacity and the number of customers left behind in the queue immediately after service initiation epochs. From this joint pgf, we extract the pgf for the number of customers in the queue and in the system respectively at service initiation epochs and departure epochs, and the pgf of the actual server capacity. Combined with additional techniques, we also obtain the pgf of the queue and system content at customer arrival epochs and random slot boundaries, and the pgf of the delay of a random customer. In the numerical experiments, we focus on the impact of correlation between the classes of consecutive customers, and on the influence of different service time distributions on the system performance. (C) 2019 Elsevier B.V. All rights reserved

Delay analysis of a variable-capacity batch-server queue with general class-dependent service times

In manufacturing, a batch server groups multiple customers that require the same type of service based on a specific characteristic, such as temperature or destination. In this paper, we extend previous work with the analysis of the delay in a variable-capacity batch-service queueing system with general class-dependent service times and customer-based correlation in the arrival process. The impact of asymmetry and correlation in the arrival process on the mean delay of a random customer and the tail distribution of the delay is investigated as well

Variable and class-dependent service capacity with a multi-class arrival process

In manufacturing, a single batch server can often group a number of customers that require the same type of service. In this paper, a shared queue without customer reordering is used in order to reduce the variability of throughput time of material throughout the manufacturing process which guarantees a global First-Come-First-Served (FCFS) service discipline. This is a significant difference with the more common polling systems where each type of customer has a dedicated queue. The batch server in this paper has a variable service capacity that depends on the classes of the customers in the queue. This paper extends previous work by considering a general number of N customer classes. During the analysis, we focus on the system occupancy of this system at random slot boundaries