openCPS: Stochastic Models for the Design and Analysis of Open-Ended Cyber-Physical Systems

计算机物理系统(CP)通常由一个或多个嵌入式设备组成，这些设备实现反馈环路以控制物理世界中的进程；因此，物理进程影响计算，反之亦然。与传统的嵌入式控制系统不同，CPS主要致力于利用物理动力学和计算之间的相互作用来提高安全性、质量和效率。因此，专门的设计和开发方法应运而生。这些方法中的绝大多数集中在封闭或有界系统上，即系统的部件或组件是固定的且先验已知的系统。然而，有一些最近即将到来的应用，如智能电网、智能交通系统、智能工厂等，其中系统往往是开放的。在这种情况下，并不是所有系统的部件或组件在运行之前都是已知的，因此，系统在设计期间不能被完全描述。开放式CP通常依赖于形成生态系统的自主移动设备。该生态系统内的联合操作提供了单独的单个设备无法实现的功能。因此，迫切需要着眼于整个生态系统的设计和开发技术和方法。一方面，这些技术和方法需要提供系统的软件工程实践，允许管理高复杂性并帮助控制所谓的紧急行为。另一方面，它们应该支持和简化时序和可靠性属性的分析和验证，特别是在需要认证的安全关键应用的环境中。来自嵌入式领域的传统设计和开发技术通常具有确定性，因此不太适合意味着某些随机性的开放式CP，即组件可能在任意时间点加入和离开系统。相比之下，使用允许使用统计和概率技术进行定时/可靠性分析和验证的随机模型似乎更有意义。最近，在文献中，已经提出了这样的方法来估计任务的最坏情况执行时间(WCET)并在存在错误的情况下提供概率可调度性保证。然而，这些工作集中在随机建模系统的一小部分和相对孤立的部分，即在一个处理器上的计算。在这个项目中，我们关注使用随机模型来进行开放式CPS的系统级设计和分析。我们打算研究将随机性纳入现有计算和通信范例的方法，使它们更适合随机建模，从而更适合统计和概率设计和分析方法。

Cyber-physical systems (CPS) typically consist of one or more embedded devices that implement feedback loops to control processes in the physical world; thereby physical processes influence computations and vice versa. In contrast to traditional embedded control systems, CPS are primarily concerned with exploiting the interplay between physical dynamics and computation towards improving safety, quality, and efficiency among others.There is a wide range of applications that can be classified as CPS. Hence, specialized design and development approaches have originated. The great majority of these approaches focus on closed or bounded systems, i.e., those where the system's parts or components are fixed and known a priori. However, there are a number of recently upcoming applications such as smart grid, intelligent transportation systems, smart factories, etc., in which systems are often open-ended. That is the case where not all system's parts or components are known prior to runtime and, as a consequence, the system cannot be fully described during design.Open-ended CPS usually rely on autonomous mobile devices that form an ecosystem. The joint operation within this ecosystem provides functionality which is otherwise unattainable by single devices in isolation. As a result, there is a strong need for design and development techniques and methods that focus on the ecosystem as a whole. On the one hand, these techniques and methods need to provide systematic software engineering practices that allow managing the high complexity and help controlling so-called emergent behavior. On the other hand, they should support and ease the analysis and validation of timing and reliability properties, in particular, in the context of safety-critical applications where certification is required.Traditional design and development techniques from the embedded domain are normally of deterministic nature and, hence, less adequate for open-ended CPS which imply certain randomness, i.e., components may join and leave the system at arbitrary points in time. In contrast, the use of stochastic models allowing statistical and probabilistic techniques for timing/reliability analysis and validation seems to be more meaningful. Lately, in the literature, such methods have been proposed for estimating the WCET (worst-case execution time) of tasks and providing probabilistic schedulability guarantees in the presence of errors. However, these works focus on stochastically modeling a small and relatively isolated part of the system, viz., computation on one processor. In this project, we are concerned with the use of stochastic models for system-level design and analysis of open-ended CPS. We intend to investigate on approaches to incorporate randomness into existing computation and communication paradigms making them more amenable to stochastic modeling and, hence, to statistical and probabilistic design and analysis methods.