Pavel Herout

Use of Distributed Traffic Simulation in the JUTS Project

In this paper, the main issues of distributed simulation in the field of urban traffic are described. This distributed simulation is based on the JUTS (Java Urban Traffic Simulator) system, which is used for modeling and analysis of traffic in cities at microscopic level of detail. Because the detailed simulation of large areas performed on a single-processor computer consumes unbearable amount of time, the possible modifications of the JUTS system for distributed computational environment are introduced.

Fault tolerance evaluation using two software based fault injection methods

A silicon independent C-Based model of the TTP/C protocol was implemented within the EU-founded project FIT. The C-based model is integrated in the C-Sim simulation environment. The main objective of this work is to verify whether the simulation model of the TTP/C protocol behaves in the presence of faults in the same way as the existing hardware prototype implementation. Thus, the experimental results of the software implemented fault injection applied in the simulation model and in the hardware implementation of the TTP/C network have been compared. Fault injection experiments in both the hardware and the simulation model are performed using the same configuration setup, and the same fault injection input parameters (fault injection location, fault type and the fault injection time). The end result comparison has shown a complete conformance of 96.30%, while the cause of the different results was due to hardware specific implementation of the built-in-self-test error detection mechanisms.

Evaluation of process controller fault tolerance using simulation

Abstract The paper presents a study of several alternatives of a fault-tolerant process controller design. We compare controller architectures based on different amount of hardware redundancy with those using time redundancy. The system behaviour is evaluated by means of a process-oriented simulation model enabling software injection of faults. As an overall measure of controller design quality (which includes both performance and reliability) we use the numerical error of the output. The results obtained on the model are used to show the dependence of the output error upon the relative speed of computation and upon the rate of faults damaging the data. Thus for every set of parameters, a system configuration which gives the best results, can be determined.

Model-Based Dependability Evaluation Method for TTP/C Based Systems

This paper presents a simulation model of the Time-Triggered Protocol (TTP/C) based embedded computer system as a tool for evaluation of system capability to tolerate a chosen category of faults. The model, being written in ANSI-C, is portable and machineindependent. Its structure is modular and flexible, so that the system to be studied and the experiment setting can easily be changed. The functionality of this model is demonstrated on a set of fault injection experiments aimed mainly to evaluate the correctness of the TTP/C specification. These experiments were done within the EU/IST FIT (Fault Injection for Time triggered architecture) project solution.

Design of a Component-Based Simulation Framework for Component Testing Using SpringDM

In this paper, we present the design of a simulation framework aimed to support testing of real components in a simulation environment. This enables thorough tests of software components without the need to create their models.

SimCo – Hybrid Simulator for Testing of Component Based Applications

Testing of component-based applications is important in order to ensure that third-party components do not compromise the functionality or properties of the whole system. However, thorough testing of functionality, behaviour and extra-functional properties is a tedious and time consuming process. In this paper we present an approach to discrete event simulation testing of components and component sets. Its unique feature is the ability to execute a mixture of real, implemented components and simulated mock-ups of the remaining parts of the application. Together, this approach allows faster testing on a wide scale of different inputs for tested components. At the same time, the use of actual components increases the confidence in the simulation test results. The approach has been implemented using the OSGi platform in the form of the SimCo framework and toolset, for which the key architectural considerations are discussed together with a short case study illustrating its usage.

Automatic Human Body Parts Detection in a 2D Anthropometric System

The paper describes the methodology of computer-based measurement for taking anthropometric dimensions. We focus on a 2D anthropometry system which is being designed for the purposes of a clothing company. The system consists of computer software, a digital camera and a background board with calibration dots. Only a few steps are needed to calibrate such a system and prepare it for the measurements. The measured person is captured, his silhouette is extracted and body dimensions are computed. Our research is intended to enrich existing techniques for automatic detection of anatomical landmarks (and body parts such as waist, chest, etc.) on the extracted silhouette. This step is very important to create a complete system without any need of user interaction and it must correspond to the body parts definitions given by clothing standards and tailors. Several potential sources of problems are discussed and some possible solutions are proposed.

Implementation of Traffic Lights in JUTS

This paper describes behaviour and implementation of light signalization in urban traffic simulator JUTS. Traffic lights are necessary part of urban traffic network and they allow using JUTS in experiments dealing with impact of time plans to traffic situation.

Verification of SimCo — Simulation tool for testing of component-based application

In software testing, most attention is given to verify the functionality of produced software. However, the quality of services (such as time to response or amount of produced data) is also important, especially in world of mobile or embedded devices. These properties are often estimated by using models of components, instead of testing the components from real applications. We have developed a simulation-based, non-invasive tool for testing and verifying characteristics of components or parts of component applications. In this paper, we present our approach to testing these properties and verification of functionality of our tool. Our approach allows testing of components without changing their implementation, as a black box objects. The results of our simulation tool are compared with results obtained from self-measuring application in order to validate the functionality of our simulation.

Probabilistic advisory system for operators can help with diagnostics of rolling mills

Advisory system for operators of complex industrial processes has been developed and improved by an international team of scientists and people from industry since 2000. Main purpose of the advisory system is to help operator set up manually adjustable parameters of an industrial process, with the aim to reach required production quality. Industrial process is taken for a stochastic process and input signals of its control system are taken for random variables. Based on Bayesian probability theory, a software toolbox was created for handling mixtures of probability density functions describing behavior of the process. Advisory system was tested and pilot application was installed on rolling mills producing metal strips. During the tests, an idea emerged to exploit verified probabilistic approach for complicated diagnostic tasks too. This diagnostics is intended for recognition of process malfunction which cannot be easily revealed by analysis of particular single signals only but analysis in multidimensional data space must be involved instead. Main principle of the advanced diagnostic method consists in finding a representation of process behavior in a short history by a mixture of probability density functions called historical mixture. Process behavior in the latest time period is represented by actual mixture. Difference between historical and actual mixtures is evaluated by calculation of Kullback-Leibler divergence. Mixtures and divergences are calculated repeatedly in time and a big change in the divergence value can be used as a source of alarm for non-standard process behavior.