Robust Real-Time System Resource Management Using Feedback

使用反馈进行稳健的实时系统资源管理

• 批准号: 0098354
• 负责人: Manimaran Govindarasu
• 金额: $ 11万
• 依托单位: Iowa State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-03-01 至 2003-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0098354&HistoricalAwards=false
• 关键词: Robust; Real; Time; System; Resource

Real-time computing is an enabling technology for many current and future application areas. Many future generations real-time systems are expected to be highly dynamic and operate in fault-prone on-deterministic environments under strict timing constraints. Therefore, these systems need to be robust while delivering high performance. This motivates the need for robust resource management techniques that dynamically address real-time requirements and provide graceful degradation in the presence of uncertainty. Despite the significant body of results in resource management in real-time systems, most of them are based on``open-loop'' strategies which are effective when the workload can be accurately modeled. These schemes are inadequate for many real world problems wherein the workload cannot be accurately modeled. Thus, there is a need for efficient architectures for resource management where predictable performance guaranteescan be obtained in the presence of uncertainty.Feedback control theory has been central to modeling systems operating in uncertain environments. In the past few decades, this theory has made impressive strides in this direction. Correct adaptation as illustrated by feedback control theory will yield significant dividends with respect to robustness. This research focuses on developing a robust resource management framework for real-time systems employing feedback controlstrategies.

实时计算是当前和未来许多应用领域的一项使能技术。许多未来的实时系统被期望是高度动态的，并在严格的时间约束下，在易发生故障的非确定性环境中运行。 因此，这些系统需要在提供高性能的同时保持稳健。这促使需要强大的资源管理技术，动态地解决实时的要求，并提供优雅的降级存在的不确定性。尽管在实时系统中的资源管理方面取得了大量成果，但其中大多数都是基于"开环“策略，当工作量可以准确建模时，这种策略是有效的。这些计划是不够的许多真实的世界的问题，其中的工作量不能准确地建模。因此，有必要为资源管理，可预测的性能profescan在不确定性的存在下获得有效的架构。反馈控制理论一直是中央建模系统在不确定的环境中运行。在过去的几十年里，这一理论在这个方向上取得了令人印象深刻的进展。 如反馈控制理论所示，正确的自适应将在鲁棒性方面产生显著的好处。 本研究的重点是开发一个强大的资源管理框架的实时系统采用反馈控制策略。