597 research outputs found
Large deviations of an infinite-server system with a linearly scaled background process
This paper studies an infinite-server queue in a Markov environment, that is, an infinite-server queue with arrival rates and service times depending on the state of a Markovian background process. We focus on the probability that the number of jobs in the system attains an unusually high value. Scaling the arrival rates ¿i¿i by a factor NN and the transition rates ¿ij¿ij of the background process as well, a large-deviations based approach is used to examine such tail probabilities (where NN tends to 88). The paper also presents qualitative properties of the system’s behavior conditional on the rare event under consideration happening. Keywords: Queues; Infinite-server systems; Markov modulation; Large deviation
Dynamic Service Rate Control for a Single Server Queue with Markov Modulated Arrivals
We consider the problem of service rate control of a single server queueing
system with a finite-state Markov-modulated Poisson arrival process. We show
that the optimal service rate is non-decreasing in the number of customers in
the system; higher congestion rates warrant higher service rates. On the
contrary, however, we show that the optimal service rate is not necessarily
monotone in the current arrival rate. If the modulating process satisfies a
stochastic monotonicity property the monotonicity is recovered. We examine
several heuristics and show where heuristics are reasonable substitutes for the
optimal control. None of the heuristics perform well in all the regimes.
Secondly, we discuss when the Markov-modulated Poisson process with service
rate control can act as a heuristic itself to approximate the control of a
system with a periodic non-homogeneous Poisson arrival process. Not only is the
current model of interest in the control of Internet or mobile networks with
bursty traffic, but it is also useful in providing a tractable alternative for
the control of service centers with non-stationary arrival rates.Comment: 32 Pages, 7 Figure
Stationary analysis of a single queue with remaining service time dependent arrivals
We study a generalization of the system (denoted by ) with
independent and identically distributed (iid) service times and with an arrival
process whose arrival rate depends on the remaining service
time of the current customer being served. We derive a natural stability
condition and provide a stationary analysis under it both at service completion
times (of the queue length process) and in continuous time (of the queue length
and the residual service time). In particular, we show that the stationary
measure of queue length at service completion times is equal to that of a
corresponding system. For we show that the continuous time
stationary measure of the system is linked to the system via a
time change. As opposed to the queue, the stationary measure of queue
length of the system at service completions differs from its marginal
distribution under the continuous time stationary measure. Thus, in general,
arrivals of the system do not see time averages. We derive formulas
for the average queue length, probability of an empty system and average
waiting time under the continuous time stationary measure. We provide examples
showing the effect of changing the reshaping function on the average waiting
time.Comment: 31 pages, 3 Figure
Analysis of Markov-modulated infinite-server queues in the central-limit regime
This paper focuses on an infinite-server queue modulated by an independently
evolving finite-state Markovian background process, with transition rate matrix
. Both arrival rates and service rates are depending
on the state of the background process. The main contribution concerns the
derivation of central limit theorems for the number of customers in the system
at time , in the asymptotic regime in which the arrival rates
are scaled by a factor , and the transition rates by a
factor , with . The specific value of
has a crucial impact on the result: (i) for the system
essentially behaves as an M/M/ queue, and in the central limit theorem
the centered process has to be normalized by ; (ii) for ,
the centered process has to be normalized by , with the
deviation matrix appearing in the expression for the variance
The NxD-BMAP/G/1 queueing model : queue contents and delay analysis
We consider a single-server discrete-time queueing system with N sources, where each source is modelled as a correlated Markovian customer arrival process, and the customer service times are generally distributed. We focus on the analysis of the number of customers in the queue, the amount of work in the queue, and the customer delay. For each of these quantities, we will derive an expression for their steady-state probability generating function, and from these results, we derive closed-form expressions for key performance measures such as their mean value, variance, and tail distribution. A lot of emphasis is put on finding closed-form expressions for these quantities that reduce all numerical calculations to an absolute minimum
Networks of Server Queues with Shot-Noise-Driven Arrival Intensities
We study infinite-server queues in which the arrival process is a Cox process
(or doubly stochastic Poisson process), of which the arrival rate is given by
shot noise. A shot-noise rate emerges as a natural model, if the arrival rate
tends to display sudden increases (or: shots) at random epochs, after which the
rate is inclined to revert to lower values. Exponential decay of the shot noise
is assumed, so that the queueing systems are amenable for analysis. In
particular, we perform transient analysis on the number of customers in the
queue jointly with the value of the driving shot-noise process. Additionally,
we derive heavy-traffic asymptotics for the number of customers in the system
by using a linear scaling of the shot intensity. First we focus on a one
dimensional setting in which there is a single infinite-server queue, which we
then extend to a network setting
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