Autonomic Middleware for Self-protection, Data Transfers, and Anomaly Analytics as a Service

该提案寻求为佛罗里达大学网站(LEAD)和亚利桑那大学网站进行的自主计算中心(CAC)研究提供资金。基础研究的资金申请由NSF批准的请愿书授权，NSF 10-507。征集邀请研究所/大学合作研究中心提交支持行业定义的基础研究的建议。本项目建议书侧重于自主计算和系统，适用于安全、故障管理和数据中心等重要领域。计划将原型部署在行业需求驱动的试验台环境中。该方案最有趣的部分是在SCADA环境中的应用，它集成了监控、多层次行为分析、决策融合和与SCADA环境安全相关的风险分析。其他领域包括自主对等系统，以及与数据中心相关的研究，包括应用层和数据中心硬件，重点是健壮性。该项目的成功完成将代表着朝着设计和部署高度安全的SCADA系统和网络迈出的重要一步。除了安全，自主检测数据中心的应用程序或子系统中的异常还可以消除对过度调配的依赖，从而解决数据中心设计中的低效问题。过度调配是一种资源效率低下的策略，通过尝试抵消任何子系统故障和故障来确保服务质量。该项目还可能对数据密集型应用程序产生更广泛的影响，这些应用程序利用临时桌面网格的可用性进行高吞吐量计算。

This proposal seeks funding for the Center for Autonomic Computing (CAC) studies conducted by the University of Florida site (lead) and the University of Arizona site. Funding Requests for Fundamental Research are authorized by an NSF approved solicitation, NSF 10-507. The solicitation invites I/UCRCs to submit proposals for support of industry-defined fundamental research. This project proposal focuses on autonomic computing and systems, applicable to the important areas of security, fault management, and data centers. Planned are the prototypes to be deployed on test bed environments driven by the requirements from industry. The most interesting part of the proposal are applications to SCADA environments, which integrate monitoring, multi-level behavior analysis, decision fusion and risk analysis relative to security of SCADA environments. Other areas include autonomic peer-to-peer systems, as well as study related to the data centers, both at the application layer and data center hardware, where focus is on robustness.The successful completion of this project will represent a significant step toward the design and deployment of highly secure SCADA systems and networks. In addition to security, the autonomic detection of anomalies in applications or subsystems of a datacenter addresses inefficiencies in data center design by eliminating the dependence on over-provisioning, which is a resource-inefficient strategy for ensuring quality of service by trying to offset any sub-system failures and malfunctions. The project has also potential for broader impact on data-intensive applications that leverage the availability of ad-hoc desktop grids for high-throughput computing.