CPS: Synergy: Collaborative Research: Safety-Feature Modeling and Adaptive Resource Management for Mixed-Criticality Cyber-Physical Systems

CPS：协同：协作研究：混合关键网络物理系统的安全特征建模和自适应资源管理

• 批准号: 1329984
• 负责人: Oleg Sokolsky
• 金额: $ 60万
• 依托单位: University of Pennsylvania
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-10-01 至 2017-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1329984&HistoricalAwards=false
• 关键词: CPS; Synergy; Collaborative; Research; Safety

To ensure operational safety of complex cyber-physical systems such as automobiles, aircraft, and medical devices, new models, analyses, platforms, and development techniques are needed that can predict, possible interactions between features, detect them in the features' concrete implementations, and either eliminate or mitigate such interactions through precise modeling and enforcement of mixed-criticality cyber-physical system semantics. This project is taking a novel approach to reasoning about and managing feature interactions in cyber-physical systems, which encompasses interactions within software, interactions through the physical dynamics of the system, and interactions via shared computational resources. The proposed approach consists of three tightly coupled research thrusts: (1) a novel way of modeling features as automata equipped with both physical dynamics of the feature environment, and an assigned criticality level in each state of an automaton, (2) new automata-theoretic and control-theoretic analysis techniques, enabled by the modeling approach, and (3) new algorithms for adaptive sharing of computational resources between individual features that are guaranteed to satisfy the assumptions made during analysis, realized within a novel mixed-criticality cyber-physical platform architecture. The modeling approach will introduce a new model for mixed-criticality cyber-physical components and will support modern development standards, such as AUTOSAR in the automotive industry, for assigning criticality levels to features. Component interfaces in this model will capture control modes and the associated physical dynamics, operating modes and the associated resource requirements and criticality level, as well as relationships between control modes and operating modes. Analysis of features expressed in the proposed model will include detection of interactions and exploration of their effect on safety properties of the composite system. The broader impacts of the proposed work are twofold. One impact lies in the pervasive use of cyber-physical systems in our society. If the developed results are adopted in industry, it may help to promote improved safety of such systems. Results of the proposed research will be used in courses offered at both University of Pennsylvania and Washington University at the graduate and undergraduate levels. The project will also provide students with opportunities to get involved in cutting edge research within their fields of study

为了确保复杂的网络物理系统（如汽车、飞机和医疗设备）的操作安全，需要新的模型、分析、平台和开发技术，这些技术可以预测功能之间可能的交互，在功能的具体实现中检测它们，并通过精确建模和执行混合关键性网络物理系统语义来消除或减轻这种交互。该项目正在采取一种新的方法来推理和管理网络物理系统中的功能交互，其中包括软件内的交互，通过系统的物理动力学的交互以及通过共享计算资源的交互。拟议的方法包括三个紧密耦合的研究重点：（1）一种将特征建模为自动机的新方法，该自动机配备有特征环境的物理动力学和自动机的每个状态中的指定关键性级别，（2）新的自动机理论和控制理论分析技术，由建模方法实现，以及（3）用于在保证满足分析期间做出的假设的个体特征之间自适应地共享计算资源的新算法，其在新颖的混合关键性网络物理平台架构内实现。 该建模方法将为混合关键性网络物理组件引入新模型，并将支持现代开发标准，例如汽车行业的AUTOSAR，用于为功能分配关键性级别。该模型中的组件接口将捕获控制模式和相关的物理动力学、操作模式和相关的资源要求和关键性级别，以及控制模式和操作模式之间的关系。所提出的模型中表示的功能分析将包括检测的相互作用和探索其对复合系统的安全性能的影响。 拟议工作的广泛影响是双重的。影响之一是网络物理系统在我们社会中的普遍使用。如果开发的结果在工业中被采用，它可能有助于促进这种系统的安全性的提高。拟议研究的结果将用于宾夕法尼亚大学和华盛顿大学的研究生和本科生课程。该项目还将为学生提供参与其研究领域前沿研究的机会