DRESD In a Nutshell July07

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The document provides an overview of the Dynamic Reconfigurability in Embedded System Design (DRESD) project. It describes the MicroLAB organization involved in DRESD, various motivations for reconfiguration, definitions of reconfiguration, examples of reconfiguration in everyday life, new frontiers for reconfigurable computing, the DRESD philosophy, involvement of DRESD at Politecnico di Milano and internationally, main DRESD projects, and opportunities to get involved.

Technology Business

DRESD in a Nutshell D ynamic R econfigurability in E mbedded S ystem D esign DRESD @ PdM – July 2007

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The engineering of large-scale cyber-physical systems (CPS) increasingly relies on principles from self-organisation and collective computing, enabling these systems to cooperate and adapt in dynamic environments. CPS engineering also often leverages digital twins that provide synchronised logical counterparts of physical entities. In contrast, sensor networks rely on the different but related concept of virtual device that provides an abstraction of a group of sensors. In this work, we study how such concepts can contribute to the engineering of self-organising CPSs. To that end, we analyse the concepts and devise modelling constructs, distinguishing between identity correspondence and execution relationships. Based on this analysis, we then contribute to the novel concept of “collective digital twin” (CDT) that captures the logical counterpart of a collection of physical devices. A CDT can also be “augmented” with purely virtual devices, which may be exploited to steer the self-organisation process of the CDT and its physical counterpart. We underpin the novel concept with experiments in the context of the pulverisation framework of aggregate computing, showing how augmented CDTs provide a holistic, modular, and cyber-physically integrated system view that can foster the engineering of self-organising CPSs.

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The technology of fusion image is dominance strongly over domain research for recent years, the techniques of fusion have various applications in real time used and proposed such as purpose of military and remote sensing etc., the fusion image is very efficient in processing of digital image. Single image produced from two images or more information of relevant combining process results from multi sensor fusion image. FPGA is the best implementation types of most technology enabling wide spread.This device works with modern versions for different critical characteristics same huge number of elements logic in order to permit complex algorithm implemented. In this paper,filters are designed and implemented in FPGA utilized for disease specified detection from images CT/MRI scanned where the samples are taken for human's brain with various medical images and the processing of fusion employed by using technique Stationary Wavelet Transform and Principal Component Analysis (SWT-PCA). Accuracy image output increases when implemented this technique and that was done by sampling down eliminating where effects blurring and artifacts doesn't influenced. The algorithm of SWT-PCA parameters quality measurements like NCC, MSE, PSNR, coefficients and Eigen values.The advantages significant of this system that provide real time, time rapid to market and portability beside the change parametric continuing in the DWT transform. The designed and simulation of module proposed system has been done by using MATLAB simulink and blocks generator system, Xilinx synthesized with synthesis tool (XST) and implemented in XilinxSpartan 6-SP605 device.

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On the way to the materialisation of the pervasive computing vision, the technological progress swelling from mobile computing and the Internet of Things (IoT) domain is already rich of missed opportunities. Firstly, coordinating large numbers of heterogeneous situated entities to achieve system-level goals in a resilient and self-adaptive way is complex and requires novel approaches to be seamlessly injected into mainstream distributed computing models. Secondly, achieving effective exploitation of computer resources is difficult, due to operational constraints resulting from current paradigms and uncomprehensive software infrastructures which hinder flexibility, adaptation, and smooth coordination of computational tasks execution. Indeed, building dynamic, context-oriented applications in small- or large-scale IoT with traditional abstractions is hard: even harder is to achieve opportunistic, QoS- and QoE-driven application task management across available hardware and networking infrastructure. In this insight paper, we analyse by the collective adaptation perspective the key directions of the impelling paradigm shift urged by forthcoming large-scale IoT scenarios. Specifically, we consider how collective abstractions and platforms can syner- gistically assist in such a transformation, by better capturing and enacting a notion of “collective service” as well as the dynamic, opportunistic, and context-driven traits of space-time-situated computations.

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