2,159 research outputs found
Lattice path counting and the theory of queues
In this paper we will show how recent advances in the combinatorics of lattice paths can be applied to solve interesting and nontrivial problems in the theory of queues. The problems we discuss range from classical ones like M^a/M^b/1 systems to open tandem systems with and without global blocking and to queueing models that are related to random walks in a quarter plane like the Flatto-Hahn model or systems with preemptive priorities. (author´s abstract)Series: Research Report Series / Department of Statistics and Mathematic
Queue-length balance equations in multiclass multiserver queues and their generalizations
A classical result for the steady-state queue-length distribution of
single-class queueing systems is the following: the distribution of the queue
length just before an arrival epoch equals the distribution of the queue length
just after a departure epoch. The constraint for this result to be valid is
that arrivals, and also service completions, with probability one occur
individually, i.e., not in batches. We show that it is easy to write down
somewhat similar balance equations for {\em multidimensional} queue-length
processes for a quite general network of multiclass multiserver queues. We
formally derive those balance equations under a general framework. They are
called distributional relationships, and are obtained for any external arrival
process and state dependent routing as long as certain stationarity conditions
are satisfied and external arrivals and service completions do not
simultaneously occur. We demonstrate the use of these balance equations, in
combination with PASTA, by (i) providing very simple derivations of some known
results for polling systems, and (ii) obtaining new results for some queueing
systems with priorities. We also extend the distributional relationships for a
non-stationary framework
A genetic approach to Markovian characterisation of H.264 scalable video
We propose an algorithm for multivariate Markovian characterisation of H.264/SVC scalable video traces at the sub-GoP (Group of Pictures) level. A genetic algorithm yields Markov models with limited state space that accurately capture temporal and inter-layer correlation. Key to our approach is the covariance-based fitness function. In comparison with the classical Expectation Maximisation algorithm, ours is capable of matching the second order statistics more accurately at the cost of less accuracy in matching the histograms of the trace. Moreover, a simulation study shows that our approach outperforms Expectation Maximisation in predicting performance of video streaming in various networking scenarios
Detecting Markov Chain Instability: A Monte Carlo Approach
We devise a Monte Carlo based method for detecting whether a non-negative
Markov chain is stable for a given set of parameter values. More precisely, for
a given subset of the parameter space, we develop an algorithm that is capable
of deciding whether the set has a subset of positive Lebesgue measure for which
the Markov chain is unstable. The approach is based on a variant of simulated
annealing, and consequently only mild assumptions are needed to obtain
performance guarantees.
The theoretical underpinnings of our algorithm are based on a result stating
that the stability of a set of parameters can be phrased in terms of the
stability of a single Markov chain that searches the set for unstable
parameters. Our framework leads to a procedure that is capable of performing
statistically rigorous tests for instability, which has been extensively tested
using several examples of standard and non-standard queueing networks
Coupled queues with customer impatience
Motivated by assembly processes, we consider a Markovian queueing system with multiple coupled queues and customer impatience. Coupling means that departures from all constituent queues are synchronised and that service is interrupted whenever any of the queues is empty and only resumes when all queues are non-empty again. Even under Markovian assumptions, the state space grows exponentially with the number of queues involved. To cope with this inherent state space explosion problem, we investigate performance by means of two numerical approximation techniques based on series expansions, as well as by deriving the fluid limit. In addition, we provide closed-form expressions for the first terms in the series expansion of the mean queue content for the symmetric coupled queueing system. By an extensive set of numerical experiments, we show that the approximation methods complement each other, each one being accurate in a particular subset of the parameter space. (C) 2017 Elsevier B.V. All rights reserved
A Stochastic Broadcast Pi-Calculus
In this paper we propose a stochastic broadcast PI-calculus which can be used
to model server-client based systems where synchronization is always governed
by only one participant. Therefore, there is no need to determine the joint
synchronization rates. We also take immediate transitions into account which is
useful to model behaviors with no impact on the temporal properties of a
system. Since immediate transitions may introduce non-determinism, we will show
how these non-determinism can be resolved, and as result a valid CTMC will be
obtained finally. Also some practical examples are given to show the
application of this calculus.Comment: In Proceedings QAPL 2011, arXiv:1107.074
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