Experimental Software Systems: Adaptware: A Design Framework for Adaptive Real-Time Systems
Experimental Software Systems: Adaptware: A Design Framework for Adaptive Real-Time Systems
批准号:
9806280
负责人:
Kang Shin
金额:
$38.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
1998
资助国家:
美国
项目状态:
已结题
起止时间:
1998-09-01 至 2002-12-31
中文摘要
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英文摘要
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.
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