43,432 research outputs found
Distributed Simulation of Heterogeneous and Real-time Systems
This work describes a framework for distributed simulation of cyber-physical systems (CPS). Modern CPS comprise large numbers of heterogeneous components, typically designed in very different tools and languages that are not or not easily composeable. Evaluating such large systems requires tools that integrate all components in a systematic, well-defined manner. This work leverages existing frameworks to facilitate the integration offers validation by simulation. A framework for distributed simulation is the IEEE High-Level Architecture (HLA) compliant tool CERTI, which provides the infrastructure for co-simulation of models in various simulation environments as well as hardware components. We use CERTI in combination with Ptolemy II, an environment for modeling and simulating heterogeneous systems. In particular, we focus on models of a CPS, including the physical dynamics of a plant, the software that controls the plant, and the network that enables the communication between controllers. We describe the Ptolemy extensions for the interaction with HLA and demonstrate the approach on a flight control system simulation
MultiVeStA: Statistical Model Checking for Discrete Event Simulators
The modeling, analysis and performance evaluation of large-scale systems are difficult tasks. Due to the size and complexity of the considered systems, an approach typically followed by engineers consists in performing simulations of systems models to obtain statistical estimations of quantitative properties. Similarly, a technique used by computer scientists working on quantitative analysis is Statistical Model Checking (SMC), where rigorous mathematical languages (typically logics) are used to express systems properties of interest. Such properties can then be automatically estimated by tools performing simulations of the model at hand. These property specifications languages, often not popular among engineers, provide a formal, compact and elegant way to express systems properties without needing to hard-code them in the model definition. This paper presents MultiVeStA, a statistical analysis tool which can be easily integrated with existing discrete event simulators, enriching them with efficient distributed statistical analysis and SMC capabilities
DynamO: A free O(N) general event-driven molecular-dynamics simulator
Molecular-dynamics algorithms for systems of particles interacting through
discrete or "hard" potentials are fundamentally different to the methods for
continuous or "soft" potential systems. Although many software packages have
been developed for continuous potential systems, software for discrete
potential systems based on event-driven algorithms are relatively scarce and
specialized. We present DynamO, a general event-driven simulation package which
displays the optimal O(N) asymptotic scaling of the computational cost with the
number of particles N, rather than the O(N log(N)) scaling found in most
standard algorithms. DynamO provides reference implementations of the best
available event-driven algorithms. These techniques allow the rapid simulation
of both complex and large (>10^6 particles) systems for long times. The
performance of the program is benchmarked for elastic hard sphere systems,
homogeneous cooling and sheared inelastic hard spheres, and equilibrium
Lennard-Jones fluids. This software and its documentation are distributed under
the GNU General Public license and can be freely downloaded from
http://marcusbannerman.co.uk/dynamo
Enabling Cross-Event Optimization in Discrete-Event Simulation Through Compile-Time Event Batching
A discrete-event simulation (DES) involves the execution of a sequence of
event handlers dynamically scheduled at runtime. As a consequence, a priori
knowledge of the control flow of the overall simulation program is limited. In
particular, powerful optimizations supported by modern compilers can only be
applied on the scope of individual event handlers, which frequently involve
only a few lines of code. We propose a method that extends the scope for
compiler optimizations in discrete-event simulations by generating batches of
multiple events that are subjected to compiler optimizations as contiguous
procedures. A runtime mechanism executes suitable batches at negligible
overhead. Our method does not require any compiler extensions and introduces
only minor additional effort during model development. The feasibility and
potential performance gains of the approach are illustrated on the example of
an idealized proof-ofconcept model. We believe that the applicability of the
approach extends to general event-driven programs
Verification of interlocking systems using statistical model checking
In the railway domain, an interlocking is the system ensuring safe train
traffic inside a station by controlling its active elements such as the signals
or points. Modern interlockings are configured using particular data, called
application data, reflecting the track layout and defining the actions that the
interlocking can take. The safety of the train traffic relies thereby on
application data correctness, errors inside them can cause safety issues such
as derailments or collisions. Given the high level of safety required by such a
system, its verification is a critical concern. In addition to the safety, an
interlocking must also ensure that availability properties, stating that no
train would be stopped forever in a station, are satisfied. Most of the
research dealing with this verification relies on model checking. However, due
to the state space explosion problem, this approach does not scale for large
stations. More recently, a discrete event simulation approach limiting the
verification to a set of likely scenarios, was proposed. The simulation enables
the verification of larger stations, but with no proof that all the interesting
scenarios are covered by the simulation. In this paper, we apply an
intermediate statistical model checking approach, offering both the advantages
of model checking and simulation. Even if exhaustiveness is not obtained,
statistical model checking evaluates with a parametrizable confidence the
reliability and the availability of the entire system.Comment: 12 pages, 3 figures, 2 table
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