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

该提案旨在为佛罗里达大学网站（牵头）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。基础研究的资助申请由NSF批准的招标（NSF 10-507）授权。 征集邀请I/UCRC提交支持行业定义的基础研究的提案。 该项目提案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。根据行业需求，计划将原型部署在测试台环境中。该提案最有趣的部分是SCADA环境的应用程序，它集成了监控，多层次的行为分析，决策融合和风险分析相对于SCADA环境的安全性。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，重点是鲁棒性。该项目的成功完成将标志着设计和部署高度安全的SCADA系统和网络迈出了重要一步。除了安全性之外，数据中心的应用或子系统中的异常的自主检测通过消除对过度供应的依赖来解决数据中心设计中的低效率，过度供应是用于通过尝试抵消任何子系统故障和失灵来确保服务质量的资源低效的策略。该项目也有可能对数据密集型应用程序产生更广泛的影响，这些应用程序利用了用于高吞吐量计算的临时桌面网格的可用性。

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.