6,639 research outputs found

    Expressing environment assumptions and real-time requirements for a distributed embedded system with shared variables

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    Apresentado na 6th IFIP TC10 Working Conference on Distributed and Parallel Embedded Systems (DIPES 2008), no âmbito do 20th IFIP World Computer Congress, Milão, Itália, set/2008.In a distributed embedded system, it is often necessary to share variables among its computing nodes to allow the distribution of control algorithms. It is therefore necessary to include a component in each node that provides the service of variable sharing. For that type of component, this paper discusses how to create a Colored Petri Nets (CPN) model that formally expresses the following elements in a clearly separated structure: (1) assumptions about the behavior of the environment of the component, (2) real-time requirements for the component, and (3) a possible solution in terms of an algorithm for the component. The CPN model can be used to validate the environment assumptions and the requirements. The validation is performed by execution of the model during which traces of events and states are automatically generated and evaluated against the requirements.(undefined

    Architecture of Environmental Risk Modelling: for a faster and more robust response to natural disasters

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    Demands on the disaster response capacity of the European Union are likely to increase, as the impacts of disasters continue to grow both in size and frequency. This has resulted in intensive research on issues concerning spatially-explicit information and modelling and their multiple sources of uncertainty. Geospatial support is one of the forms of assistance frequently required by emergency response centres along with hazard forecast and event management assessment. Robust modelling of natural hazards requires dynamic simulations under an array of multiple inputs from different sources. Uncertainty is associated with meteorological forecast and calibration of the model parameters. Software uncertainty also derives from the data transformation models (D-TM) needed for predicting hazard behaviour and its consequences. On the other hand, social contributions have recently been recognized as valuable in raw-data collection and mapping efforts traditionally dominated by professional organizations. Here an architecture overview is proposed for adaptive and robust modelling of natural hazards, following the Semantic Array Programming paradigm to also include the distributed array of social contributors called Citizen Sensor in a semantically-enhanced strategy for D-TM modelling. The modelling architecture proposes a multicriteria approach for assessing the array of potential impacts with qualitative rapid assessment methods based on a Partial Open Loop Feedback Control (POLFC) schema and complementing more traditional and accurate a-posteriori assessment. We discuss the computational aspect of environmental risk modelling using array-based parallel paradigms on High Performance Computing (HPC) platforms, in order for the implications of urgency to be introduced into the systems (Urgent-HPC).Comment: 12 pages, 1 figure, 1 text box, presented at the 3rd Conference of Computational Interdisciplinary Sciences (CCIS 2014), Asuncion, Paragua

    Initiating organizational memories using ontology-based network analysis as a bootstrapping tool

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    An important problem for many kinds of knowledge systems is their initial set-up. It is difficult to choose the right information to include in such systems, and the right information is also a prerequisite for maximizing the uptake and relevance. To tackle this problem, most developers adopt heavyweight solutions and rely on a faithful continuous interaction with users to create and improve content. In this paper, we explore the use of an automatic, lightweight ontology-based solution to the bootstrapping problem, in which domain-describing ontologies are analysed to uncover significant yet implicit relationships between instances. We illustrate the approach by using such an analysis to provide content automatically for the initial set-up of an organizational memory

    A Parallel Distributed Strategy for Arraying a Scattered Robot Swarm

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    We consider the problem of organizing a scattered group of nn robots in two-dimensional space, with geometric maximum distance DD between robots. The communication graph of the swarm is connected, but there is no central authority for organizing it. We want to arrange them into a sorted and equally-spaced array between the robots with lowest and highest label, while maintaining a connected communication network. In this paper, we describe a distributed method to accomplish these goals, without using central control, while also keeping time, travel distance and communication cost at a minimum. We proceed in a number of stages (leader election, initial path construction, subtree contraction, geometric straightening, and distributed sorting), none of which requires a central authority, but still accomplishes best possible parallelization. The overall arraying is performed in O(n)O(n) time, O(n2)O(n^2) individual messages, and O(nD)O(nD) travel distance. Implementation of the sorting and navigation use communication messages of fixed size, and are a practical solution for large populations of low-cost robots

    An architecture-based dependability modeling framework using AADL

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    For efficiency reasons, the software system designers' will is to use an integrated set of methods and tools to describe specifications and designs, and also to perform analyses such as dependability, schedulability and performance. AADL (Architecture Analysis and Design Language) has proved to be efficient for software architecture modeling. In addition, AADL was designed to accommodate several types of analyses. This paper presents an iterative dependency-driven approach for dependability modeling using AADL. It is illustrated on a small example. This approach is part of a complete framework that allows the generation of dependability analysis and evaluation models from AADL models to support the analysis of software and system architectures, in critical application domains
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