640 research outputs found
Performance evaluation of an emergency call center: tropical polynomial systems applied to timed Petri nets
We analyze a timed Petri net model of an emergency call center which
processes calls with different levels of priority. The counter variables of the
Petri net represent the cumulated number of events as a function of time. We
show that these variables are determined by a piecewise linear dynamical
system. We also prove that computing the stationary regimes of the associated
fluid dynamics reduces to solving a polynomial system over a tropical
(min-plus) semifield of germs. This leads to explicit formul{\ae} expressing
the throughput of the fluid system as a piecewise linear function of the
resources, revealing the existence of different congestion phases. Numerical
experiments show that the analysis of the fluid dynamics yields a good
approximation of the real throughput.Comment: 21 pages, 4 figures. A shorter version can be found in the
proceedings of the conference FORMATS 201
Analysis of Timed and Long-Run Objectives for Markov Automata
Markov automata (MAs) extend labelled transition systems with random delays
and probabilistic branching. Action-labelled transitions are instantaneous and
yield a distribution over states, whereas timed transitions impose a random
delay governed by an exponential distribution. MAs are thus a nondeterministic
variation of continuous-time Markov chains. MAs are compositional and are used
to provide a semantics for engineering frameworks such as (dynamic) fault
trees, (generalised) stochastic Petri nets, and the Architecture Analysis &
Design Language (AADL). This paper considers the quantitative analysis of MAs.
We consider three objectives: expected time, long-run average, and timed
(interval) reachability. Expected time objectives focus on determining the
minimal (or maximal) expected time to reach a set of states. Long-run
objectives determine the fraction of time to be in a set of states when
considering an infinite time horizon. Timed reachability objectives are about
computing the probability to reach a set of states within a given time
interval. This paper presents the foundations and details of the algorithms and
their correctness proofs. We report on several case studies conducted using a
prototypical tool implementation of the algorithms, driven by the MAPA
modelling language for efficiently generating MAs.Comment: arXiv admin note: substantial text overlap with arXiv:1305.705
Max-plus algebra in the history of discrete event systems
This paper is a survey of the history of max-plus algebra and its role in the field of discrete event systems during the last three decades. It is based on the perspective of the authors but it covers a large variety of topics, where max-plus algebra plays a key role
Mean-Payoff Optimization in Continuous-Time Markov Chains with Parametric Alarms
Continuous-time Markov chains with alarms (ACTMCs) allow for alarm events
that can be non-exponentially distributed. Within parametric ACTMCs, the
parameters of alarm-event distributions are not given explicitly and can be
subject of parameter synthesis. An algorithm solving the -optimal
parameter synthesis problem for parametric ACTMCs with long-run average
optimization objectives is presented. Our approach is based on reduction of the
problem to finding long-run average optimal strategies in semi-Markov decision
processes (semi-MDPs) and sufficient discretization of parameter (i.e., action)
space. Since the set of actions in the discretized semi-MDP can be very large,
a straightforward approach based on explicit action-space construction fails to
solve even simple instances of the problem. The presented algorithm uses an
enhanced policy iteration on symbolic representations of the action space. The
soundness of the algorithm is established for parametric ACTMCs with
alarm-event distributions satisfying four mild assumptions that are shown to
hold for uniform, Dirac and Weibull distributions in particular, but are
satisfied for many other distributions as well. An experimental implementation
shows that the symbolic technique substantially improves the efficiency of the
synthesis algorithm and allows to solve instances of realistic size.Comment: This article is a full version of a paper accepted to the Conference
on Quantitative Evaluation of SysTems (QEST) 201
Limit theorems for iterated random topical operators
Let A(n) be a sequence of i.i.d. topical (i.e. isotone and additively
homogeneous) operators. Let be defined by and
. This can modelize a wide range of systems including,
task graphs, train networks, Job-Shop, timed digital circuits or parallel
processing systems. When A(n) has the memory loss property, we use the spectral
gap method to prove limit theorems for . Roughly speaking, we show
that behaves like a sum of i.i.d. real variables. Precisely, we show
that with suitable additional conditions, it satisfies a central limit theorem
with rate, a local limit theorem, a renewal theorem and a large deviations
principle, and we give an algebraic condition to ensure the positivity of the
variance in the CLT. When A(n) are defined by matrices in the \mp semi-ring, we
give more effective statements and show that the additional conditions and the
positivity of the variance in the CLT are generic
Hybrid modeling and optimization of biological processes
Proß S. Hybrid modeling and optimization of biological processes. Bielefeld: Bielefeld University; 2013
Modelling, reduction and analysis of Markov automata (extended version)
Markov automata (MA) constitute an expressive continuous-time compositional modelling formalism. They appear as semantic backbones for engineering frameworks including dynamic fault trees, Generalised Stochastic Petri Nets, and AADL. Their expressive power has thus far precluded them from effective analysis by probabilistic (and statistical) model checkers, stochastic game solvers, or analysis tools for Petri net-like formalisms. This paper presents the foundations and underlying algorithms for efficient MA modelling, reduction using static analysis, and most importantly, quantitative analysis. We also discuss implementation pragmatics of supporting tools and present several case studies demonstrating feasibility and usability of MA in practice
- …