CAREER: Building Resilient Internet Services with Learning and Control

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。由于Internet的动态性和前所未有的规模，Internet服务对底层网络系统提出了包括可伸缩性、可靠性和可用性在内的挑战。CAREER项目专注于通过机器学习和控制技术构建能够应对这些挑战的互联网服务。因特网服务建立在规模和复杂性不断增长的基于集群的计算机系统之上。这样的系统变得如此复杂，以至于要很好地理解整个系统的动态行为是一个很大的挑战。研究人员采用分析和有组织的方法，在网络系统上设计自主软件基础设施，用于构建弹性互联网服务。该项目利用统计学习建立经验模型，以帮助克服网络系统中规模和复杂性的挑战。在多层集群上设计了具有端到端服务质量的协调接纳控制和容量规划算法。模型无关控制技术与经验模型一起用于分配资源和动态重新配置系统以满足性能优化需求。它开发了性能区分、隔离和自适应重新配置功能，以增强系统可靠性和可用性。它通过在数据中心实验室中开发一个测试平台来演示用于自动安排、协调和管理复杂计算机系统、中间件和服务的设计技术的编排，从而扩大了研究的影响。研究结果将以技术报告的形式向公众散发。该项目还支持一个新的跨学科安全工程博士项目。

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).Due to the dynamic nature and unprecedented scale of the Internet, Internet services pose challenges including scalability, reliability, and availability to underlying networked systems. This CAREER project concentrates on building Internet services that are resilient to those challenges with machine learning and control techniques. Internet services build upon cluster-based computer systems that keep growing in scale and complexity. Such systems become so complicated that it is even a big challenge to get a good understanding of the entire system dynamic behaviors. The investigators take an analytical and organized approach to design an autonomous software infrastructure on networked systems for building resilient Internet services. The project builds empirical models using statistical learning to help overcome the challenges of scale and complexity in networked systems. It designs coordinated admission control and capacity planning algorithms with end-to-end quality-of-service on multi-tier clusters. Model-independent control techniques are used with empirical models to allocate resources and to dynamically reconfigure the system for performance optimization needs. It develops performance differentiation, isolation, and self-adaptive reconfiguration capabilities for enhancing system reliability and availability. It broadens the research impact by developing a testbed in a data center lab to demonstrate the orchestration of designed techniques for automated arrangement, coordination, and management of complex computer systems, middleware, and services. The research results will be disseminated to the public as technical reports. This project also supports a new inter-disciplinary Ph.D. of Engineering in security program.