III-COR-Small: Towards More Flexible, Expressive and Robust Stream Systems

该奖项是根据2009年《美国复苏和再投资法案》(Public Law 111-5)资助的。当前的流引擎大多是独立系统，而在许多应用中，流处理将是更大的信息系统的一个组件。与用户界面、交易数据和档案等其他组件的结合将变得越来越重要。为了使流查询在延长的执行期内保持健壮，它们必须具有适应内部和外部更改的方法。输入速率、时间延迟和数据分布的变化可能会导致内部内存和处理负载发生变化。运营商必须适应当地的这些变化，并与其他运营商协调一致。客户需求的变化为改善资源使用创造了机会，运营商必须适应这一点。为了使流处理系统在面对不断变化的工作负载和可能的系统故障时保持健壮，体系结构必须具有当前不存在的灵活性和适应性级别。该团队提出了三种方法来开发必要的灵活性。他们将使用正式的分析，提供准确的时间和进度概念，以便为各种情况提供标准和衡量标准。此外，他们将详细说明操作员和架构设计活动，然后在两个不同的数据流系统中实施和评估这些活动。除了波特兰州立大学的教师和那里的研究生，该团队还与AT&&T Research进行了持续的合作，AT&T Research将为测试新系统提供通道。该项目开发的技术将扩大数据流系统可以合理服务的应用程序的数量，通过与商业系统合作，将加快将这些技术应用到下一代产品中。除了一门关于蒸汽系统的新课程外，该团队每年夏天都会与波特兰州立大学通过周六学院项目招聘的高中实习生合作。

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).Current stream engines are mostly stand-alone systems, whereas in many applications, stream processing will be one component of a larger information system. Coupling with other components, such as user interfaces, transactional data and archives will be increasingly important. For stream queries to be robust over extended execution periods, they must have the means to adapt to both internal and external changes. Changes in input rates, time lags and data distributions can cause shifts in internal memory and processing loads. Operators must adapt to these changes both local and in concert with other operators. Variations in client demands create opportunities for improved resource use to which operators must adapt. For a stream processing system to be robust in the face of changing workloads and possible system faults, the architecture must have levels of flexibility and adaptivity not currently existing. The team proposes three approaches to developing the necessary flexibility. They will use a formal analysis that will provide precise notions of time and progress, in order to provide criteria and metrics for a variety of situations. In addition, they will elaborate operator and architecture design activities that will then be implemented and evaluated in two different data stream systems. In addition to faculty at Portland State University and graduate students there, the team has an ongoing collaboration with AT&T Research, who will provide access for testing the new system. The techniques developed on this project will broaden the number of applications that can be reasonably served with data stream systems, and by working with commercial systems, the adoption of those techniques into next-generation products will be accelerated. In addition to a new course in steam systems, the team works with high school interns each summer, who are recruited through the Saturday Academy program at Portland State.