ITR: Querying Sequentially Accessed XML Data

以XML形式交换的大容量数据流对于科学、政府和商业领域的广泛应用来说正变得至关重要。然而，利用它们带来了重大的技术挑战和机遇。首先，流查询需要在内存中执行计算，与任意大的数据流相比，内存有限。第二，网络带宽的快速增长超过了CPU到内存和CPU到磁盘传输速率的增长。其结果是，高带宽网络传输流数据的速度将比传统方法处理的速度更快。高效的动态数据流处理是必要的。该项目将开发一种以XML形式查询数据流的综合方法，涵盖从正式基础到系统的所有范围。该项目的预期结果将是一种全新的架构、技术和查询处理器，可用于XML数据流，并对广泛的应用程序产生影响。该方法将在Roadnet项目提供的地震数据上进行测试。然而，我们预计这项研究将对大量的XML数据流产生更广泛的影响。

High-volume data streams exchanged in XML form are becoming crucial to a wide range of applications in the scientific, government and business domains. However, taking advantage of them raises significant technical challenges and opportunities. First, stream queries require computations to be performed in memory that is limited with comparison to the arbitrarily large data stream. Second, the rapid increase of network bandwidths surpasses the increase of CPU-to-memory and CPU-to-disk transfer rates. The result is that high bandwidth networks will be delivering stream data faster than they can be processed by conventional approaches. Efficient on-the-fly data stream processing is necessary. This project will develop a comprehensive approach to querying data streams in XML form, covering the spectrum from formal foundations all the way to systems. The expected outcome of the project will be a qualitatively new architecture, technology and query processor for XML data streams, with impact on a wide range of applications. The approach will be tested on seismic data provided by the ROADNet project. However, we expect that the research will have broader impact on voluminous XML data streams.