The GI/M/1 queue and the GI/Geo/1 queue both with single working vacation

We first consider the continuous-time GI/M/1 queue with single working vacation (SWV). During the SWV, the server works at a different rate rather than completely stopping working. We derive the steady-state distributions for the number of customers in the system both at arrival and arbitrary epochs, and for the FIFO sojourn time for an arbitrary customer. We then consider the discrete-time GI/Geo/1/SWV queue by contrasting it with the GI/M/1/SWV queue.     

On asymptotics of the emptiness probability in the M/GI/1 queue

We obtain the asymptotic estimation for the non-stationary emptiness probability in the M/GI/1 queue for the case of regularly varying tails of service-time distribution.     

Analytic and computational analysis of the discrete-time GI/D-MSP/1 queue using roots

This paper presents a simple closed-form analysis for evaluating system-length distributions at various epochs of the discrete-time GI/D-MSP/1 queue. The proposed analysis is based on roots of the associated characteristic equation of the vector-generating function of system-length distribution at prearrival epochs. We provide the steady-state system-length distribution at random epoch by using the classical argument based on Markov renewal theory. The queueing-time distribution has also been investigated. Numerical aspects have been tested for a variety of interarrival- and service-time distributions and a sample of numerical outputs is presented.     

Optimal priorities in GI|Gn|1 queue

A polynomial-time algorithm based on reduction to a polyhedron minimization problem is proposed for minimizing a given function F(W₁,...,W_n) that depends on the mean waiting times in the Gl|G_n|l queue.Translated from Kibernetika, No. 2, pp. 80–85, March–April, 1991.     

A polynomial factorization approach to the discrete time GI/G/1/(N) queue size distribution

The queue of a single server is considered with independent and identically distributed interarrivai and service times and an infinite (GI/G/1) or finite (GI/G/1/N) waiting room. The queue discipline is non-preemptive and independent of the service times.

A discrete time version of the system is analyzed, using a two-component state model at the arrival and departure instants of customers. The equilibrium equations are solved by a polynomial factorization method. The steady state distribution of the queue size is then represented as a linear combination of geometrical series, whose parameters are evaluated by closed formulae depending on the roots of a characteristic polynomial.

Considering modified boundary constraints, systems with finite waiting room or with an exceptional first service in each busy period are included.     

Analysis of a finite-buffer bulk-service queue under Markovian arrival process with batch-size-dependent service

We consider a finite capacity single server queue in which the customers arrive according to a Markovian arrival process. The customers are served in batches following a ‘general bulk service rule’. The service times, which depend on the size of the batch, are generally distributed. We obtain, in steady-state, the joint distribution of the random variables of interest at various epochs. Efficient computational procedures in the case of phase type services are presented. An illustrative numerical example to bring out the qualitative nature of the model is presented.     

Switched poisson process/g/1 queue with service interruptions

In this paper, we develop an expression for the expected waiting time in a single server queueing system subject to interruptions with alternately varying Poisson arrival and renewal service rates. This queueing system is useful to model situations in production, computer and telecommunication systems in which customer arrivals and service requirements differ depending on whether the server is working or not. We develop an expression for the expected waiting time by approximating the virtual delay process by a Brownian motion. Our approximation for the expected waiting time involves only the means and variances and does not depend on any assumptions regarding the interarrival, service or switching time distributions. We present simulation results to illustrate the quality of our approximations.     

Steady state analysis of the GI/M/1/N queue with a variant of multiple working vacations

This paper studies the GI/M/1/N queue with a variant of multiple working vacations, where the server leaves for a working vacation as soon as the system becomes empty. The server takes at most H consecutive working vacations if the system remains empty after the end of a working vacation. Employing the supplementary variable and embedded Markov chain methods, we obtain the queue length distribution at different time epochs. Based on the various system length distribution, the probability of blocking, mean waiting times and mean system lengths have been derived. Finally, numerical results are discussed.     

A note on varying lattice isotropy

We note how certain topological features of finite regular triangular lattice (hexagonal tiling) can be used to model most effectively various degrees of the lattice isotropy. This is illustrated with the example of simulating the process of two-dimensional unconditional spreading from a single cluster of the lattice sites.     

A Markovian queue with varying number of servers and applications to the performance comparison of HSDPA user equipment

Inspired by the need for performability models for HSDPA user equipment, a Markovian queue with varying number of servers is conceived. The arrival and the service processes, the number of allocated or active servers of the queue are inherently, and independently (or jointly) Markov modulated. Batch arrivals, batch services, autocorrelation of inter-arrival times, and autocorrelation of batch sizes can be accommodated in the queue, by a suitable use of Markov modulation and generalized exponential distribution. The queue has a provision for negative customers too. Transformations of the balance equations into a computable form are proposed in order to obtain the steady state probabilities with the Spectral Expansion method. This queue is used to model the High Speed Downlink Packet Access (HSDPA) wireless networks. The model is an integrated one with respect to HSDPA, capable of accommodating many of the intricate aspects of HSDPA such as, channel allocation policy, loss of packets due to channel fading, bursty and correlated traffic. Good agreement is observed between the numerical results of the proposed analytical model and those of an independent simulator of real HSDPA and radio channel behaviors. The comparison of the terminal categories specified by the 3rd Generation Partnership Project (3GPP) is also presented.     

The departure process of an N/G/1 queue

The departure process of an N/G/1 queue is investigated. The arrival process called an N process is a versatile point process and includes, for example, a Markov-modulated Poisson process, which is comprised of models of packetized voice and video traffic arrival processes. The first passage analysis yields LSTs of distributions of the interdeparture times. Emphasis is on the interdeparture times of an N/D/1 queue. Numerical examples show that correlation of interarrival times is likely to be preserved in interdeparture times, and that the departure of a voice packet multiplexer can be expected to be smoothed for a normal load. The result in this paper enables evaluation of the smoothing effect of burst traffic through nodes in Asynchronous Transfer Mode networks.     

Moments of the queue size distribution in the MAP/G/1 retrial queue

We consider an MAP/G/1 retrial queue. A necessary and sufficient condition is obtained for the existence of the moments of the queue size distribution. The condition is expressed in terms of the moment condition for a service time distribution. In addition, we provide recursive formulas for the moments of the queue size distribution. Numerical examples are given to illustrate our results.     

Duration of the buffer overflow period in a batch arrival queue

The buffer overflow period is the remaining service time upon reaching a full buffer in a finite-buffer single server queueing system. Its distribution is an important characteristic of the queue, as this is the period in which arriving cells are lost. In this paper detailed studies of the buffer overflow period in a batch arrival queue are presented. Theoretical results are illustrated via numerical examples.     

Loss behavior in space priority queue with batch Markovian arrival process — discrete-time case

This paper applies matrix-analytic approach to the examination of the loss behavior of a space priority queue. In addition to the evaluation of the long-term high-priority and low-priority packet loss probabilities, we examine the bursty nature of packet losses by means of conditional statistics with respect to critical and non-critical periods that occur in an alternating manner. The critical period corresponds to having more than a certain number of packets in the buffer; non-critical corresponds to the opposite. Hence there is a threshold buffer level that splits the state space into two. By such a state-space decomposition, two hypothesized Markov chains are devised to describe the alternating renewal process. The distributions of various absorbing times in the two hypothesized Markov chains are derived to compute the average durations of the two periods and the conditional high-priority packet loss probability encountered during a critical period. These performance measures greatly assist the space priority mechanism for determining a proper threshold. The overall complexity of computing these performance measures is of the order O(K²m₁³m₂³), where K is the buffer capacity, and m₁ and m₂ are the numbers of phases of the underlying Markovian structures for the high-priority and low-priority packet arrival processes, respectively. Thus the results obtained are computationally tractable and numerical results show that, by choosing a proper threshold, a space priority queue not only can maintain the quality of service for the high-priority traffic but also can provide the near-optimum utilization of the capacity for the low-priority traffic.     

A note on pseudorandom number generators

PRNGs may be compared to antibiotics. Every type of generator has its unwanted side-effects. There are no safe generators. Good random number generators are characterized by theoretical support, convincing empirical evidence, and positive pratical aspects. They will produce correct results in many - though not all - simulations.Important open questions in this field concern reliable parallelization, the creation of good generators on demand, and the mathematical foundation of forecasting the empirical performance by theoretical figures of merit.Three safety-measures for numerical practice are recommended: (a) check simulation results with widely different generators before taking them seriously, (b) avoid to combine, vectorize, or parallelize PRNGs without theoretical and empirical support, and (c) get to know the properties of your preferred PRNGs.