Experimental Software Systems: Adaptware: A Design Framework for Adaptive Real-Time Systems

[806280] shin, Kang G.Jahanian， farnam密歇根大学安娜堡实验软件系统：ADAPTWARE：自适应实时系统的设计框架本项目旨在设计、实现和评估一个名为ADAPTWARE的软件框架，该框架由架构支持、资源管理机制和编程抽象组成，用于使服务质量（QoS）适应动态波动的资源容量和需求。通过提供构建可重用的多用途实时软件组件所需的基础设施，该框架将减少实时软件开发的成本和时间。就像今天的消费者可以从不同的供应商那里购买软件和硬件组件，并根据他们的需要构建一个计算环境一样，这个框架可以提供构建和集成实时系统组件的方法，以保持它们的时间正确性，同时使动态计算与可用资源相称的可预测的端到端时间保证成为可能。我们计划通过构建一个测试平台并在测试平台上执行具有代表性的应用程序来演示我们的框架的好处，这些应用程序来自软实时系统（如多媒体）和硬实时系统（如自动飞行）。通过将实时应用程序设计与目标平台上的资源容量假设分离，从而促进平台容量、配置或负载的更改，这些应用程序的软件开发成本有望显著降低。该项目还演示了我们对平台容量的抽象（远离程序员）如何帮助构建实时系统，通过动态地调整应用程序QoS以适应可用资源，从而能够容忍一系列违反其负载和故障假设的情况。

9806280Shin, Kang G.Jahanian, FarnamThe University of Michigan at Ann Arbor Experimental Software Systems: ADAPTWARE: A Design Framework for Adaptive Real-Time SystemsThis project is to design, implement, and evaluate a software framework, called the Adaptware, that consists of architectural support, resource-management mechanisms, and programming abstractions for adapting Quality-of-Service (QoS) to dynamically-fluctuating resource capacity and demands. This framework will reduce the cost and time of real-time software development by providing the infrastructure necessary for building reusable multi-purpose real-time software components. In much the same way as today's consumers can buy software and hardware components from different vendors and construct a computing environment tailored to their needs, this framework can provide the means of building and integrating real-time system components so as to preserve their temporal correctness while making it possible to dynamically compute predictable end-to-end temporal guarantees commensurate with available resources. We plan to demonstrate the benefits of our framework by building a testbed and executing representative applications on the testbed, drawn from both soft real-time systems such as multimedia, and hard real-time systems such as automated flight. Software development costs of these applications are expected to be reduced significantly by separating real-time application design from resource-capacity assumptions on the target platform, hence facilitating changes in platform capacity, configuration or load. This project is also to demonstrate how our abstraction of platform capacity (away from the programmer) can help build real-time systems that can tolerate a range of violations of their load and failure hypotheses by adapting application QoS dynamically to the resources available.