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（公法111-5）资助的。目前的流引擎大多是独立的系统，而在许多应用中，流处理将是一个更大的信息系统的一个组成部分。与用户界面、交易数据和档案等其他组成部分的结合将越来越重要。 为了使流查询在延长的执行周期内保持健壮，它们必须具有适应内部和外部变化的方法。 输入速率、时间滞后和数据分布的变化可能会导致内部存储器和处理负载的变化。 运营商必须适应这些变化，无论是本地的还是与其他运营商的合作。客户需求的变化创造了改善资源利用的机会，运营商必须适应这些机会。 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鲁棒性，该架构必须具有当前不存在的灵活性和自适应性。 该小组提出了三种方法来发展必要的灵活性。 他们将使用正式的分析，提供精确的时间和进度概念，以便为各种情况提供标准和度量。此外，他们还将详细阐述运营商和架构设计活动，然后在两个不同的数据流系统中实施和评估。 除了波特兰州立大学的教师和那里的研究生外，该团队还与AT T Research进行了持续的合作，AT T Research将提供测试新系统的机会。 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数量，通过与商业系统合作，将加速将这些技术应用于下一代产品。 除了蒸汽系统的新课程外，该团队每年夏天还与高中实习生合作，他们是通过波特兰州立大学的星期六学院项目招募的。

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.