Scalable Multidimensional Indexing

信息技术的快速发展导致了对多媒体对象的存储、管理、访问和使用的需求增加。本研究项目的目标是构建一个可扩展的多媒体对象分布式存储库。高维是多媒体对象的一个重要特征，由于计算和I/O的增加，可能会显著增加搜索开销。研究的一个组成部分是使用动态和增量变换来减少搜索维数。此外，还建立了性能模型，该模型可以针对不同的用户对查全率和查准率的期望来预测这种降维的效果。研究的另一个目标是在分布式系统上分离索引结构和关联数据。这提高了性能以及故障情况下的可用性。构建能够响应常见访问和查询模式的自适应索引结构也是研究的一个组成部分。该项目还在审查用户对数据一致性的要求，并支持多媒体对象的不同程度的一致性。该项目的成果将以科学论文和可下载软件的形式传播。该项目将导致建立有效的索引结构，并在总体上更好地理解多媒体数据的可伸缩查询。

Rapid advances in information technology have led to increased demand for the storage, management, access, and use of multimedia objects. The goal of this research project is to construct a scalable distributed repository for multimedia objects. The high number of dimensions, an important feature of multimedia objects, can significantly increase the search overhead due to increased computations and I/O. One component of the research is to reduce the number of search dimensions using dynamic and incremental transforms. This is supplemented with a performance model that can predict the effect of such dimensionality reduction for different user expectations of recall and precision. Another goal of the research is to decluster the index structure and the associated data on a distributed system. This improves performance as well as availability in case of failures. Building adaptive index structures that can respond to common access and query patterns is also a component of the research. The project is also examining user requirements with respect to consistency of data and supporting different levels of consistency for multimedia objects. The results of the project will be disseminated in the form of scientific papers and software that can be downloaded. The project will lead to efficient index structures and, in general, to better understanding of scalable querying of multimedia data.