191 research outputs found

    Multicriteria optimal reconfiguration of fault-tolerant real-time tasks

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    International audienceWe propose a technique for discrete controller synthesis, with optimal synthesis on bounded paths, in order to model, design, and optimize fault-tolerant distributed systems, taking into account several criteria (e.g., the execution costs of the tasks and their quality of service). Different combinations are explored for multi-criteria optimizatio

    A novel approach to fault tolerant multichannel networks designing problems

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    This work presents solution of a bus interconnection network set designing task on the base of a hypergraph model. In order to do this the interconnection network is presented as a multipartite hypergraph. A system with virtual bus connections functioning in an environment of common physical channel was analyzed, which is characteristic of the networks based on the WDM technology. The mathematical reliability model was proposed for two modes of system functioning: with redundancy of communication subsystem and division of communication load. As solution estimation criteria the expected changes of processing efficiency changes were used as also a communication delay change criteria and system reliability criteria. The designing task solution is searched in a Pareto set composed of Pareto optima. The selection procedure of a specific solution in the case of its equivalency in relation to a vector goal function was presented

    A Motif-based Mission Planning Method for UAV Swarms Considering Dynamic Reconfiguration

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    Influenced by complex terrain conditions of combat environments and constrained by the level of communication technology, communication among unmanned aerial vehicles (UAV) is greatly restricted. In light of this situation, mission planning for UAV swarms under limited communication has become a difficult problem. This paper introduces motifs as the basic unit of configuration and proposes a motif-based mission planning method considering dynamic reconfiguration. This method uses multidimensional dynamic list scheduling algorithm to generate a mission planning scheme based on the motif-based swarm configuration solution. Then it incorporates order preserved operators with NSGA-III algorithm to find Pareto front solutions of all possible mission planning schemes. The feasibility of this mission planning method is validated through a case study

    Autonomic Management of Reconfigurable Embedded Systems using Discrete Control: Application to FPGA

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    This paper targets the autonomic management of dynamically partially reconfigurable hardware architectures based on FPGAs. Such hardware-level autonomic computing has been less often studied than at software-level. We consider control techniques to model the considered behaviours of the computing system and derive a controller for the control objective enforcement. Discrete Control modelled with Labelled Transition Systems is employed in this paper. Such models are amenable to Discrete Controller Synthesis algorithms that can automatically generate a controller enforcing the correct behaviours of a controlled system. A general modelling framework is proposed for the control of FPGA based computing systems. We consider system application described as task graphs and FPGA as a set of reconfigurable areas that can be dynamically partially reconfigured to execute tasks. We encode the computation of an autonomic manager as a DCS problem w.r.t. multiple constraints and objectives e.g., mutual exclusion of resource uses, power cost minimization. We validate our models and manager computations by using the BZR language and an experimental demonstrator implemented on a Xilinx FPGA platform.Nous traitons de la gestion autonomique des architectures matérielles dynamique- ment et partiellement reconfigurables á base de FPGAs. Cette forme d'informatique autonomique au niveau matériel a été moins souvent étudié qu'au niveau logiciel. Nous considérons des tech- niques de contrôle pour modéliser les comportements du système de calcul et pour dériver un contrôleur pour le maintien de l'objectif de contrôle. Nous utilisons des techniques de contrôle discret modélisé avec des systèmes de transition étiquetés. Ces modèles se prêtent à une algorith- mique de synthèse de contrôleurs discrets (SCD) qui peut générer automatiquement un contrôleur qui force les comportements corrects d'un système contrôlé. Un cadre général de modélisation est proposé pour le contrôle des systèmes informatiques à base de FPGA. Nous considérons que l'application est décrite par un graphes de tâches, et le FPGA comme un ensemble de zones reconfigurables, qui peuvent être dynamiquement et partiellement reconfigurées pour exécuter des tâches. Nous formulons le calcul d'un gestionnaire autonomique comme un problème de SCD concernant des contraintes et objectifs multiples, par exemple, l'exclusion mutuelle de l'utilisation des ressources, la minimisation du coût en énergie. Nous validons nos modèles et les calculs du gestionnaire en utilisant le langage BZR et un démonstrateur expérimental mis en œuvre sur une plate-forme FPGA Xilinx

    A Modeling and Analysis Framework To Support Monitoring, Assessment, and Control of Manufacturing Systems Using Hybrid Models

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    The manufacturing industry has constantly been challenged to improve productivity, adapt to continuous changes in demand, and reduce cost. The need for a competitive advantage has motivated research for new modeling and control strategies able to support reconfiguration considering the coupling between different aspects of plant floor operations. However, models of manufacturing systems usually capture the process flow and machine capabilities while neglecting the machine dynamics. The disjoint analysis of system-level interactions and machine-level dynamics limits the effectiveness of performance assessment and control strategies. This dissertation addresses the enhancement of productivity and adaptability of manufacturing systems by monitoring and controlling both the behavior of independent machines and their interactions. A novel control framework is introduced to support performance monitoring and decision making using real-time simulation, anomaly detection, and multi-objective optimization. The intellectual merit of this dissertation lies in (1) the development a mathematical framework to create hybrid models of both machines and systems capable of running in real-time, (2) the algorithms to improve anomaly detection and diagnosis using context-sensitive adaptive threshold limits combined with context-specific classification models, and (3) the construction of a simulation-based optimization strategy to support decision making considering the inherent trade-offs between productivity, quality, reliability, and energy usage. The result is a framework that transforms the state-of-the-art of manufacturing by enabling real-time performance monitoring, assessment, and control of plant floor operations. The control strategy aims to improve the productivity and sustainability of manufacturing systems using multi-objective optimization. The outcomes of this dissertation were implemented in an experimental testbed. Results demonstrate the potential to support maintenance actions, productivity analysis, and decision making in manufacturing systems. Furthermore, the proposed framework lays the foundation for a seamless integration of real systems and virtual models. The broader impact of this dissertation is the advancement of manufacturing science that is crucial to support economic growth. The implementation of the framework proposed in this dissertation can result in higher productivity, lower downtime, and energy savings. Although the project focuses on discrete manufacturing with a flow shop configuration, the control framework, modeling strategy, and optimization approach can be translated to job shop configurations or batch processes. Moreover, the algorithms and infrastructure implemented in the testbed at the University of Michigan can be integrated into automation and control products for wide availability.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147657/1/migsae_1.pd

    The safety case and the lessons learned for the reliability and maintainability case

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    This paper examine the safety case and the lessons learned for the reliability and maintainability case

    Proceedings of the 5th International Workshop on Reconfigurable Communication-centric Systems on Chip 2010 - ReCoSoC\u2710 - May 17-19, 2010 Karlsruhe, Germany. (KIT Scientific Reports ; 7551)

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    ReCoSoC is intended to be a periodic annual meeting to expose and discuss gathered expertise as well as state of the art research around SoC related topics through plenary invited papers and posters. The workshop aims to provide a prospective view of tomorrow\u27s challenges in the multibillion transistor era, taking into account the emerging techniques and architectures exploring the synergy between flexible on-chip communication and system reconfigurability

    Engineering Subsystems Analysis of Adaptive Small Satellites

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    The current point-based satellite electronic subsystem engineering design process is insufficient to address the dynamic operations and post-mission reuse of small satellites. Also, space systems and missions require an adaptive architecture(s) that can withstand the radiation-prone flight environment and respond to in-situ environmental changes using onboard resources while maintaining optimal performance. This enormous conceptual design variables space/task of highly adaptive small satellite (HASS) system can be too large to explore, study, analyse and qualify. This research involved a parametric electronic subsystem engineering design process and methodology development for the production of sustainable capability-based small satellites. Consequently, an adaptive multifunctional architecture with five levels of in-orbit spacecraft customisations that eliminate subsystem boundaries at the system level is presented. Additive manufacturing methods are favoured to fabricate the proposed adaptive multifunctional monolithic structures. The initial system engineering analyses reveal that the HASS system has mass-, cost- and power-savings over the conventional small satellite implementation. An adaptive small satellite link performance improvement satisfying a less than 2 dB link margin loss for a 0.1 dB in-band noise figure ripple has been established. Moreover, a power budget model for HASSs that ensures a reliable solar array design and eliminates undue equipment oversizing has been developed. An adaptive broadband beamformer that can improve the satellite link margin has been designed. Also, an estimating relationship has been developed and practically validated for the operational times analysis of small satellite subsystems. The reported novel findings promise to enable capability-based, adaptive, cost-effective, reliable, multifunctional, broadband and optimal-performing space systems with recourse to post-mission re-applications

    Towards Applying Logico-numerical Control to Dynamically Partially Reconfigurable Architectures

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    International audienceWe investigate the opportunities given by recent developments in the context of Discrete Controller Synthesis algorithms for infinite, logico-numerical systems. To this end, we focus on models employed in previous work for the management of dynamically partially reconfigurable hardware architectures. We extend these models with logico-numerical features to illustrate new modeling possibilities, and carry out some benchmarks to evaluate the feasibility of the approach on such models
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