Model‐based MPI‐IO tuning with Periscope tuning framework

For many parallel applications, I/O performance is a major bottleneck. MPI‐IO, defined by the MPI forum, can help parallel applications overcome the performance and portability limitations of existing parallel I/O interfaces. Although autotuning has been used to improve the performance of computing kernels, MPI‐IO autotuning has rarely been studied. To automate MPI‐IO performance tuning, we designed and implemented an automatic tuner. The tuner relies on the Periscope tuning framework for transparently passing hints to the MPI‐IO library and for automatically collecting performance data. Unlike computational code, each MPI‐IO function takes a relatively long time to complete. Thus, exhaustively searching through the entire parameter space is impractical. So we developed a performance model that can direct us to shorten the tuning time. Copyright © 2015 John Wiley & Sons, Ltd.     

Model‐based design of IoT systems with the BIP component framework

The design of software for networked systems with nodes running an Internet of things operating system faces important challenges due to the heterogeneity of interacting things and the constraints stemming from the often limited amount of available resources. In this context, it is hard to build confidence that a design solution fulfills the application's requirements. This paper introduces a design flow for web service applications of the representational state transfer style that is based on a formal modeling language, the behaviour, interaction, priority (BIP) component framework. The proposed flow applies the principles of separation of concerns in a component‐based design process that supports the modular design and reuse of model artifacts. The BIP tools for state‐space exploration allow verifying qualitative properties for service responsiveness, ie, the timely handling of events. Moreover, essential quantitative properties are validated through statistical model checking of a stochastic BIP model. All properties are preserved in actual implementation by ensuring that the deployed code is consistent with the validated model. We illustrate the design of a representational state transfer sense‐compute‐control application for a Wireless Personal Area Network architecture with nodes running the Contiki operating system. The results validate qualitative and quantitative properties for the system and include the study of error behaviours.     

Model‐based code generation for HLA federates

This paper addresses the problem of automated code generation for a High Level Architecture compliant federate application given its behavior model. The behavior model is a part of the architectural model of a federation that the federate can participate in. The federate behavior model is based on Live Sequence Charts, adopted as the behavioral specification formalism in the Federation Architecture Metamodel (FAMM). FAMM serves as a formal language for describing federation architectures. An objective is to help the testing of federation architecture by means of its prototype implementation early in the development lifecycle. A further objective is to help developers construct complete federate applications that are well modularized. The approach to achieve these objectives is aspect‐oriented in that the generated code, which handles the federate's interactions with a federation execution, serves as the base code, where the computation logic is to be weaved as an aspect. Copyright © 2009 John Wiley & Sons, Ltd.     

Model‐based security testing: a taxonomy and systematic classification

Model‐based security testing relies on models to test whether a software system meets its security requirements. It is an active research field of high relevance for industrial applications, with many approaches and notable results published in recent years. This article provides a taxonomy for model‐based security testing approaches. It comprises filter criteria (i.e. model of system security, security model of the environment and explicit test selection criteria) as well as evidence criteria (i.e. maturity of evaluated system, evidence measures and evidence level). The taxonomy is based on a comprehensive analysis of existing classification schemes for model‐based testing and security testing. To demonstrate its adequacy, 119 publications on model‐based security testing are systematically extracted from the five most relevant digital libraries by three researchers and classified according to the defined filter and evidence criteria. On the basis of the classified publications, the article provides an overview of the state of the art in model‐based security testing and discusses promising research directions with regard to security properties, coverage criteria and the feasibility and return on investment of model‐based security testing. Copyright © 2015 John Wiley & Sons, Ltd.     

Linear Model‐based Feedforward Control for Improving Tracking‐performance of Linear Motors

The main purpose of this article is to propose a linear model‐based approach for improving the tracking performance of linear motors. In particular, P‐ and PI‐controllers, augmented with a linear‐model‐based feedforward controller and disturbance observer (DOB), were utilized in this research. Experimental results show that the feedforward controller can substantially reduce the phase‐delay problem resulting from the limitation of closed‐loop bandwidth. In addition, the DOB can reject nonlinear behaviors to keep a motor‐system close to our nominal linear model. Compared with the results of using P‐ and PI‐controllers only, tracking errors were reduced from 4.44% to 0.67% of the desired trajectory. Therefore, the proposed method provides a solution for improving the tracking performance of linear motors.     

A probabilistic framework for component‐based vector graphics

We propose a framework for data‐driven manipulation and synthesis of component‐based vector graphics. Using labelled vector graphical images of a given type of object as input, our processing pipeline produces training data, learns a probabilistic Bayesian network from that training data, and offer various data‐driven vector‐related tools using synthesis functions. The tools ranges from data‐driven vector design to automatic synthesis of vector graphics. Our tools were well received by designers, our model provides good generalisation performance, also from small data sets, and our method for synthesis produces vector graphics deemed significantly more plausible compared with alternative methods.     

Model‐based event‐triggered control for linear plant with threshold variable and model states

This paper studies the robustness of model‐based event‐triggered control systems with respect to the differences between the plant and model matrices. Two types of event conditions, which involve an additional threshold variable and the norm of model states, are investigated, respectively. The tunable parameters in both the event conditions are designed according to the differences between the plant and model matrices. Also, the uncertainties in the plant matrices are considered, and the asymptotic stability can be guaranteed robustly. Moreover, the relationship between the tunable parameters and the model matrices is revealed. Namely, on the one hand, there exists a range of the tunable parameters such that the closed‐loop system is asymptotically stable with model matrices in any compact set. On the other hand, if the differences between the plant and model matrices are small enough, the tunable parameters can be set arbitrarily large. Finally, a numerical example is provided to illustrate the efficiency and feasibility of the obtained results. Copyright © 2016 John Wiley & Sons, Ltd.     

A component‐based framework for radio‐astronomical imaging software systems

This paper describes a component‐based framework for radio‐astronomical imaging software systems. We consider optimal re‐use strategies for packages of disparate architectures brought together within a modern component framework. In this practical case study, the legacy codes include both procedural and object‐oriented architectures. We consider also the special requirements on scientific component middleware, with a specific focus on high‐performance computing. We present an example application in this component architecture and outline future development planned for this project. Copyright © 2007 John Wiley & Sons, Ltd.     

A Learning‐Theoretic Approach To Model‐Set Identification

A new approach to model‐set identification is proposed based on an agnostic learning theory. The squared prediction error is estimated together with its uncertainty uniformly in some parameter region. Based on this estimation, a model set is constructed so as to include the best model. The proposed approach does not require assumptions on the true dynamics or the noise, neither does it need infinite number of input‐output data in order to justify its result. But it guarantees that the size of the identified model set converges to zero as the number of input‐output data increases. Improvement of the precision is considered on the proposed identification method. Generalization of the approach is discussed and a numerical example is presented.     

Model‐based event‐triggered predictive control for networked systems with communication delays compensation

This paper addresses the model‐based event‐triggered predictive control problem for networked control systems (NCSs). Firstly, we propose a discrete event‐triggered transmission scheme on the sensor node by introducing a quadratic event‐triggering function. Then, on the basis of the aforementioned scheme, a novel class of model‐based event‐triggered predictive control algorithms on the controller node is designed for compensating for the communication delays actively and achieving the desired control performance while using less network resources. Two cases, that is, the value of the communication delay of the first event‐triggered state is less or bigger than the sampling period, are considered separately for certain NCSs, regardless of the communication delays of the subsequent event‐triggered states. The codesign problems of the controller and event‐triggering parameter for the two cases are discussed by using the linear matrix inequality approach and the (switching) Lyapunov functional method. Furthermore, we extended our results to the NCSs with systems uncertainties. Finally, a practical ball and beam system is studied numerically to demonstrate the compensation effect for the communication delays with the proposed novel model‐based event‐triggered predictive control scheme. Copyright © 2014 John Wiley & Sons, Ltd.     

A duality based framework for integrating reliability and precision for sensor network design

In sensor network design literature, requirements such as maximization of the network reliability [Y. Ali, S. Narasimhan, Sensor network design for maximizing reliability of linear processes, AIChE J. 39 (1993) 820–828; Y. Ali, S. Narasimhan, Redundant sensor network design for linear processes, AIChE J. 41 (1995) 2237–2249] and minimization of cost subject to precision constraints [M. Bagajewicz, Design and retrofit of sensor networks in process plants, AIChE J. 43 (1997) 2300–2306; M. Bagajewicz, E. Cabrera, New MILP formulation for instrumentation network design and upgrade, AIChE J. 48 (2002) 2271–2282] have been proposed as a criteria for optimally locating sensors. In this article, we show that the problems of maximizing reliability and maximizing precision (or minimizing variance) for linear processes are dual of each other. To achieve this duality, we propose transformations which can be used to convert sensor failure probabilities into equivalent sensor variances and vice versa. Thus, the duality enables working in a single framework with specified criteria on reliability as well as precision. As an application of this duality, we propose two formulations for the sensor network design problem viz., maximization of the network reliability subject to precision constraints and minimization of the network variance subject to reliability constraints. We also show the utility of these formulations to determine the pareto-front for the combinatorial sensor network design problem. Hydrodealkylation and steam-metering case studies are used to illustrate the proposed ideas.     

A quality‐of‐service‐based framework for creating distributed heterogeneous software components

Component‐based software development offers a promising solution for taming the complexity found in today's distributed applications. Today's and future distributed software systems will certainly require combining heterogeneous software components that are geographically dispersed. For the successful deployment of such a software system, it is necessary that its realization, based on assembling heterogeneous components, not only meets the functional requirements, but also satisfies the non‐functional criteria such as the desired quality of service (QoS). In this paper, a framework based on the notions of a meta‐component model, a generative domain model and QoS parameters is described. A formal specification based on two‐level grammar is used to represent these notions in a tightly integrated way so that QoS becomes a part of the generative domain model. A simple case study is described in the context of this framework. Copyright © 2002 John Wiley & Sons, Ltd.     

Model‐to‐model and model‐to‐text: looking for the automation of VigilAgent

VigilAgent is a methodology for the development of agent‐oriented monitoring applications that uses agents as the key abstraction elements of the involved models. It has not been developed from scratch, but it reuses fragments from Prometheus and INGENIAS methodologies for modelling tasks and the ICARO framework for implementation purposes. As VigilAgent intends to automate as much as possible the development process, it exploits. Model transformation techniques are one of the key aspects of the model‐driven development approach. A model‐to‐model transformation is used to facilitate the interoperability between Prometheus and INGENIAS methodologies. Also, a model‐to‐text transformation is performed to generate ICARO code from the INGENIAS model. A case study based on access control is used to illustrate the fundamentals of the model‐to‐model and model‐to‐text transformations implemented in VigilAgent.     

Creating user‐generated content for location‐based learning: an authoring framework

Two recent emerging trends are that of Web 2.0, where users actively create content and publish it on the Web, and also location awareness, where a digital device utilizes a person's physical location as the context to provide specific services and/or information. This paper examines how these two phenomena can be brought together so that user‐generated content on mobile devices is used to provide informal learning opportunities relevant to a person's location. However, the generative process of such media does not always have much guidance on how or what to create, so the quality of such information can be highly variable. To overcome this, a framework has been designed to guide the authoring of user‐generated content so that it can be used for informal learning about one's immediate surroundings (particularly in an outdoor setting), combining pedagogical aspects with those from human–computer interaction and environmental aesthetics. The framework consists of six dimensions that include aspects such as curriculum area (e.g. science, art), type of communication, use of language/media related to the landscape, knowledge level of content, contextual aspects, and types of interaction. In order to test the framework before it could be used to scaffold new content, it was first used to analyse and evaluate over 200 items of existing user‐generated content, to investigate the appropriateness of the proposed dimensions and the items contained therein or if any were missing. This paper presents the findings of this initial testing phase, together with a discussion of how the framework can be improved, in order to help scaffold the creation of new user‐generated content in the future.     

High reliability leadership: A conceptual framework

Although it is assumed that leaders can be extremely important in enhancing safe operations, little is known about how they actually contribute to high reliability organizing. This study proposes a conceptual framework for leadership in High Reliability Organizations (HROs) based on theory and previous empirical research. It identifies leadership behaviours that contribute to six organizing facets in HROs, from which two leadership behavioural categories are extracted: leading expansion and leading reaction. Behaviours included in both categories might be potentially beneficial practices for leaders working in high‐hazard industries. The framework provides the basis for future theory development and debate.     

Model‐centric software architecture reconstruction

Much progress has been achieved in defining methods, techniques, and tools for software architecture reconstruction (SAR). However, less progress has been achieved in constructing reasoning frameworks from existing systems that support organizations in architecture analysis and design decisions. These reasoning frameworks are necessary, for example, to assemble existing components and deploy them in new system configurations. We propose a model‐centric approach where this kind of reasoning is driven by the analysis of quality attribute scenarios. The scenarios and the related quality attribute models guide the SAR effort by focusing on the elicitation of model relevant artifacts. The approach further drives the model construction towards the analytical support of What If scenarios that explore responses stimulated by new requirements, such as new deployments of existing components. The paper provides two real‐world case studies. The first case study introduces the model‐centric reconstruction approach in the context of a large satellite tracking system. The second case study provides the construction of a time performance model for an existing embedded system in the automotive industry. The model allows us to perform cost‐efficient predictions of component assemblies in new customer configurations. Copyright © 2005 John Wiley & Sons, Ltd.     

Model‐based fault detection and isolation method using ART2 neural network

This article presents a model‐based fault diagnosis method to detect and isolate faults in the robot arm control system. The proposed algorithm is composed functionally of three main parts: parameter estimation, fault detection, and isolation. When a change in the system occurs, the errors between the system output and the estimated output cross a predetermined threshold, and once a fault in the system is detected, the estimated parameters are transferred to the fault classifier by the adaptive resonance theory 2 neural network (ART2 NN) with uneven vigilance parameters for fault isolation. The simulation results show the effectiveness of the proposed ART2 NN–based fault diagnosis method. © 2003 Wiley Periodicals, Inc.