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Systèmes reconfigurables et auto-organisés : architecture et implantation

Abstract : Increasing needs of computation power, flexibility and interoperability are making systems more and more difficult to integrate and to control. The high number of possible configurations, alternative design decisions or the integration of additional functionalities in a working system cannot be done only at the design stage any more. In this context, where the evolution of networked systems is extremely fast, different concepts are studied with the objective to provide more autonomy and more computing power. This work proposes a new approach for the utilization of reconfigurable hardware in a self-organised context. A concept and a working system are presented as Reconfigurable Self-Organised Systems (RSS). The proposed hardware architecture aims to study the impact of reconfigurable FPGA based systems in a self-organised networked environment and partial reconfiguration is used to implement hardware accelerators at runtime. The proposed system is designed to observe, at each level, the parameters that impact on the performances of the networked self-adaptive nodes. The results presented here aim to assess how reconfigurable computing can be efficiently used to design a complex networked computing system and the state of the art allowed to enlighten and formalise characteristics of the proposed self-organised hardware concept. Its evaluation and the analysis of its performances were possible using a custom board: the Potsdam Intelligent Camera System (PICSy). It is a complete implementation from the electronic board to the control application. To complete the work, measurements and observations allow analysis of this realisation and contribute to the common knowledge
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Submitted on : Thursday, March 29, 2018 - 12:00:56 PM
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  • HAL Id : tel-01749095, version 1



Kevin Cheng. Systèmes reconfigurables et auto-organisés : architecture et implantation. Autre. Université Paul Verlaine - Metz, 2011. Français. ⟨NNT : 2011METZ039S⟩. ⟨tel-01749095⟩



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