Model-Based Verification and Estimation Framework for Dynamically Partially Reconfigurable Systems
Model-Based Verification and Estimation Framework for Dynamically Partially Reconfigurable Systems
复制标题
DOI：
10.1109/tii.2011.2123901
复制
发表时间：
2011-03
影响因子：
12.3
通讯作者：
Chun-Hsian Huang;Pao-Ann Hsiung
中科院分区：
文献类型：
--
作者：
Chun-Hsian Huang;Pao-Ann Hsiung
统一建模语言（UML），一个行业事实上的标准，已被用来分析动态部分可重构系统（DPRS），可以重新配置其硬件功能的需求在运行时。为了使模型驱动架构（MDA）更现实，适用于在工业环境中的DPRS设计，基于模型的验证和评估（MOVE）框架，提出了这项工作。通过利用DPRS的固有特点，并考虑实时系统的要求，一个半自动的模型翻译器转换的UML模型的DPRS时间自动机模型的转换紧迫性语义的模型检查。在此基础上，提出了一个基于UML的软硬件协同设计平台（UCoP），以支持UML模型与真实的硬件体系结构之间的直接交互。两阶段的验证过程，包括详尽的功能验证和物理感知的性能估计，是完全基于模型，从而减少系统验证工作。我们使用了一个动态部分可重构的网络安全系统（DPRNSS）作为案例研究。相关实验表明，MOVE中的模型检测器可以缓解状态空间爆炸问题的影响。与具有范围从-43.4%至18.4%的不准确度的基于合成的估计方法相比，UCoP可以通过实际时间测量提供准确且高效的特定于平台的验证和估计。
Unified Modeling Language (UML), an industry de-facto standard, has been used to analyze dynamically partially reconfigurable systems (DPRS) that can reconfigure their hardware functionalities on-demand at runtime. To make model-driven architecture (MDA) more realistic and applicable to the DPRS design in an industrial setting, a model-based verification and estimation (MOVE) framework is proposed in this work. By taking advantage of the inherent features of DPRS and considering real-time system requirements, a semiautomatic model translator converts the UML models of DPRS into timed automata models with transition urgency semantics for model checking. Furthermore, a UML-based hardware/software co-design platform (UCoP) is proposed to support the direct interaction between the UML models and the real hardware architecture. The two-phase verification process, including exhaustive functional verification and physical-aware performance estimation, is completely model-based, thus reducing system verification efforts. We used a dynamically partially reconfigurable network security system (DPRNSS) as a case study. The related experiments have demonstrated that the model checker in MOVE can alleviate the impact of the state-space-explosion problem. Compared to the synthesis-based estimation method having inaccuracies ranging from -43.4% to 18.4%, UCoP can provide accurate and efficient platform-specific verification and estimation through actual time measurements.