The M/G-G/1 Oscillating Queueing System

In this paper oscillating queueing system is studied. Oscillating queueing systems are interesting practical objects and researches in this subject are a natural continuation of previous studies on oscillating stochastic processes. It is shown a powerful method for finding characteristic quantities of queuing systems (potential method). Using this method the steady-state distribution of the length of the queue in the M/G-G/1 oscillating system is found and presented in explicit formula. In addition, a numerical example is given.     

On the loss process in a batch arrival queue

In this paper, we investigate the loss process in a finite-buffer queue with batch arrivals and total rejection discipline. In such a model, if the buffer has insufficient capacity to accept all the customers included in an arriving batch, the whole batch is blocked and lost. This scheme is especially useful in performance evaluation of buffering processes in IP (internet protocol) networks. The main result of this paper is a closed-form formula for the joint distribution of the length of the first lost series of batches and the time of the first loss. Moreover, the limiting distribution (as the buffer size grows to infinity) is shown.     

Queues with Dropping Functions and Autocorrelated Arrivals

We present an analysis of the queueing system in which arriving jobs are dropped with probability depending on the queue size. The arrivals are assumed to be autocorrelated and they are modeled by the Markov-modulated Poisson process. Both transient and stationary distributions of the queue size, as well as the system loss ratio and throughput are obtained. The analytical results are accompanied with numerical examples based on the autocorrelated traffic recorded in an IP computer network.     

On the Remaining Service Time upon Reaching a Given Level in M/G/1 Queues

The ability of effectively finding the distribution of the remaining service time upon reaching a target level in M/G/1 queueing systems is of great practical importance. Among other things, it is necessary for the estimation of the Quality-of-Service (QoS) provided by Asynchronous Transfer Mode (ATM) networks. The previous papers on this subject did not give a comprehensive solution to the problem. In this paper an explicit formula for this distribution is given. This formula is general as it includes any initial level of the length of the queue, any type of service distribution (heavy tails) and any traffic intensity ρ. Moreover, it is easy to use and fast in computation. To show this several numerical examples are presented. In addition, a solution of the similar problem in G/M/1 queues (which is the distribution of the remaining interarrival time) is given.