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。由于互联网的动态性和前所未有的规模，互联网服务对底层网络系统提出了包括可扩展性，可靠性和可用性在内的挑战。 这个CAREER项目专注于构建能够通过机器学习和控制技术应对这些挑战的互联网服务。 互联网服务建立在基于集群的计算机系统上，这些系统的规模和复杂性不断增长。 这样的系统变得如此复杂，以至于很好地理解整个系统的动态行为甚至是一个很大的挑战。 研究人员采取分析和组织的方法来设计网络系统上的自主软件基础设施，以构建弹性互联网服务。 该项目使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。 它设计了协调的接纳控制和容量规划算法与端到端的服务质量的多层集群。 模型独立控制技术与经验模型一起使用，以分配资源并动态地重新配置系统以满足性能优化的需要。 它开发了性能区分，隔离和自适应重新配置功能，以提高系统的可靠性和可用性。 它通过在数据中心实验室中开发测试平台来扩展研究影响，以展示复杂计算机系统，中间件和服务的自动化安排，协调和管理的设计技术的编排。 研究结果将作为技术报告向公众散发。 该项目还支持一个新的跨学科博士。安全工程专业

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.