Run-time environment for resource-scarce networked systems

处理器、内存和不同系统类别(移动节点、地面节点)的输入/输出的动态资源管理以及由此产生的潜在的系统软件动态适配(自适应运行时环境，ARTE)是研究工作的重点。除了动态适应的面向应用的原因外，考虑(移动)节点的系统能量状态作为这种适应的触发器尤其重要。正在开发的能量模型不仅适用于单个孤立节点，而且适用于由移动节点和地面节点组成的分布式整个系统，包括它们相互作用所产生的(能量)成本。基于这些能量模型，对(部分)程序代码的(最坏情况)能耗进行了预测。特别是，系统需要随时通过优化和动态的适应能力来代表生物应用对环境变化和变化的要求做出反应。为了管理和分配所需的重新配置和重新编程任务，正在开发一种跨所有系统类别的分布式中间件。为了最大限度地提高整个系统的能源意识，正在使用以前开发的(能源)分析工具，以能源意识的方式开发低级系统组件。借助模块的静态分析、能量分析和动态适应，可以在运行时利用目标平台的节能和能量收集机制，并在能源短缺的情况下促进异常处理决策。在开发结束时，提供了提供高度灵活性的动态适应性、能源感知系统。

The dynamic resource management of processor, memory, and input/output of the different system classes (mobile nodes, ground nodes) as well as the resulting, potentially dynamic adaptation of the system software (adaptive run-time environment, ARTE) are in the focus of the research work. Besides application-oriented reasons for dynamic adaptations, it is especially important to consider the system's energy state of (mobile) nodes as a trigger for such adaptations. Energy models are being developed not only for single, isolated nodes but also for the distributed overall system that consists of mobile and ground nodes including (energy) costs resulting from their interactions. Based on these energy models, the (worst-case) energy consumption of (partial) program code is predicted. In particular, the system needs to react to environmental changes and varying requirements on behalf of the biologic applications by means of optimized and dynamic adaptation capabilities at any time. A distributed middleware, which stretches across all system classes, is being developed in order to manage and distribute required reconfiguration and reprogramming tasks. To maximize the energy awareness of the overall system, low-level system components are being developed in an energy-aware manner by using previously developed (energy) analysis tools. With the aid of the modules static analysis, energy analysis, and dynamic adaptation it is possible to exploit energy-saving and energy-harvesting mechanisms of the target platforms at run-time and, in case of energy shortage, to facilitate exception-handling decisions. At the end of the development, a dynamically adaptable, energy-aware system is available which provides a high degree of flexibility.