High Throughput I/O for Large Scale Data Repositories

包括地理信息系统、科学可视化和多维数据库在内的许多应用程序都包含高达TB大小的大型数据存储库。虽然TB级的存储空间现在是可以实现的，但有效的检索是一个具有挑战性的问题。 该研究涉及新的计划，以并行磁盘之间的数据分配，以提高检索效率，包括计划使用复制，高效的检索算法和自组织计划，以适应磁盘故障，磁盘添加和不断变化的查询patterns.Declustering在过去几年中吸引了很多的兴趣，并在许多领域，包括高维数据管理，地理信息系统和科学可视化的应用。 大多数去聚类研究都集中在空间范围查询和寻找最坏情况下的加性误差低的方案。本研究探讨各个方面的去聚，包括新的去聚计划，复制去聚，异构去聚，自适应去聚和去聚使用多个数据库。调查人员从理论和实践两方面着手处理每一个问题，研究什么是理论上可能的，什么是实践中可以实现的，并试图缩小两者之间的差距。研究人员研究了具有坚实理论基础的新的去簇方案，包括数论去簇和设计理论去簇。研究了空间范围查询和任意查询的复制策略。设计理论复制的检索算法具有线性复杂度，并保证最坏情况下的检索成本。 研究人员研究检索复杂性和检索成本之间的权衡，并开发一套检索协议。这项研究涉及自适应去集群计划，适应磁盘故障，磁盘添加和改变查询类型的磁盘之间移动桶在空闲期间。

Many applications including geographical information systems, scientific visualization and igh-dimensional databases include large data repositories up to terabytes in size. Although terabytes of storage space is now achievable, efficient retrieval is a challenging problem. This research involves novel schemes to distribute data among parallel disks for efficient retrieval including schemes using replication, efficient retrieval algorithms and self-organizing schemes that adapt to disk failures, disk additions and changing query patterns.Declustering has attracted a lot of interest over the last few years and has applications in many areas including high-dimensional data management, geographical information systems and scientific visualization. Most of the declustering research have focused on spatial range queries and finding schemes with low worst-case additive error. This research investigates various aspects of declustering including novel declustering schemes, replicated declustering, heterogeneous declustering, adaptive declustering and declustering using multiple databases. The investigators approach every issue both theoretically and practically, study what is theoretically possible, what can be achieved in practice and try to close the gap between the two. The investigators study novel declustering schemes with solid theoretical foundations including number-theoretic declustering and design-theoretic declustering. Replication strategies for various types of queries including spatial range queries and arbitrary queries are studied. Retrieval algorithm for design-theoretic replication has linear complexity and guarantees worst-case retrieval cost. The investigators study tradeoffs in retrieval between complexity and retrieval cost and develop a suite of protocols for retrieval. This research involves adaptive declustering schemes that adapt to disk failures, disk additions and changing query types by moving buckets between disks during idle periods.