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

该方案描述了一种在运行时执行多分辨率系统行为监控并基于该监控在专用分布式和并行系统中生成模型的方法。这项研究的重点是专用系统，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。将重点介绍以下三个具体的子领域：多分辨率行为监控数据融合灵活的行为建模这项工作的智力价值是以一种可以接受的方式进一步理解高速网络上工作的协作处理器内的异常检测。该提案还包括持续的产业合作，以及完成和启动博士学位论文，以及让历史上代表性不足的群体参与一个夏季研究项目。

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.