An Adaptive Integrated Behavior Monitoring and Modeling Approach for High Performance/High Speed Network Computing Environments

高性能/高速网络计算环境的自适应集成行为监控和建模方法

• 批准号: 0430354
• 负责人: Rayford Vaughn
• 金额: --
• 依托单位: Mississippi State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-10-01 至 2009-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0430354&HistoricalAwards=false
• 关键词: Adaptive; Integrated; Behavior; Monitoring; Modeling

This proposal describes an approach to performing multi-resolution system behavior monitoring at runtime and generating models based on this monitoring in dedicated distributed and parallel systems. The research offered focuses on dedicated systems, particularly clusters performing a well-known set of tasks that occur with relatively predictable frequency. Anomaly detection can be accomplished through comparison of the observed runtime system behavior against a high-fidelity model of the system. The following three specific sub-areas will be emphasized:Multi-resolution Behavior MonitoringData FusionFlexible Behavior ModelingThe intellectual merit of this work is to further understanding of anomaly detection within cooperating processors working over high speed networks in such a way that the resulting overhead is acceptable. The proposal also includes a continuing industrial collaboration, as well as the completion and initiation of PhD dissertations and involvement of historically underrepresented groups in a summer research program.

本提案描述了一种在专用的分布式和并行系统中执行多分辨率系统行为监控并基于此监控生成模型的方法。研究提供的重点是专用系统，特别是执行一组众所周知的任务的集群，这些任务以相对可预测的频率发生。异常检测可以通过将观察到的运行时系统行为与系统的高保真模型进行比较来完成。以下三个具体的子领域将被强调：多分辨率行为监测数据融合灵活的行为建模这项工作的智力价值是进一步理解在高速网络上工作的协作处理器内的异常检测，以这种方式产生的开销是可以接受的。该提案还包括持续的工业合作，以及完成和启动博士论文，并让历史上代表性不足的群体参与夏季研究项目。