Optimal data structures for organization and retrieval of spatial data

本研究将探讨分布式网络环境下空间数据的存储、检索和动态更新的最佳方法。空间数据通常用于描述地理和地理空间信息。本研究将探讨如何以最佳方式组织、分发和复制数据，以支持有效的可搜索性，从而增强数据可用性。这项研究非常有必要。目前存在大量空间数据，包括卫星（如雷达卫星）图像、地理制图、航空视像检查和天气观测，并不断收集新的空间数据。事实上，最近传感器技术的进步已经使收集的数据量增加了几个数量级。这些大型集合只能以分布式方式托管在网络环境中的多个主机上，可以是本地的，也可以是远程的。这带来了一系列需要解决的研究问题，主要是：-地理信息系统的空间数据结构和算法的设计，尽可能低的内存占用，并且仍然允许诸如节点添加和删除，节点锁定，范围查询等操作有效地执行。- I/O感知的空间数据结构，对内存层次结构中不同的访问成本很敏感，包括与分布式、远程和辅助存储成本相关的问题。-分布式空间数据结构的缓存策略，以协调索引结构的分页，以减少外部（网络或磁盘）访问给定用户请求的变化。-分布式海量空间数据结构中的一致性、复制和可恢复性问题。-数据管理和地理空间数据的组织方式，以保持访问的效率，数据的准确性，以及分发数据的能力。-设计用于存储大量数据的数据结构，这些数据可以很容易地在网络上分布。

This research will investigate optimal approaches for the storage, retrieval and dynamic updating spatial data in a distributed networked environment. Spatial data are commonly used to describe, among other applications, geographic and geospatial information. This research will investigate how to optimally organize, distribute and replicate data as to support efficient searchability and as a consequence enhance data availability. There is a strong need for this research. Large stores of spatial data now exist, including satellite (e.g. RADARSAT) imagery, geographical mapping, aerial video inspection and weather observations, with new spatial data continually being gathered. Indeed, recent advances in sensor technology have led to an increase of several orders of magnitude in the amount of data collected. These large collections can only be hosted in a distributed manner across several hosts in a networked environment, either locally or remotely. This brings a host of research questions that need to be addressed, chiefly: - The design of spatial data structures and algorithms for geographic information systems that have as low a memory footprint as possible and still allow operations such as node additions and removals, node locking, range queries to be performed efficiently. - I/O aware spatial data structures that are sensitive to varying access costs across the memory hierarchy, including issues related to the cost of distributed, remote and secondary storage. - Caching strategies for distributed spatial data structures that to coordinate paging of indexing structures in order to reduce external (network or disk) accesses given changes in user requests. - Issues of consistency, replication and recoverability in distributed massive spatial data structures. - Data management and organization of geo-spatial data in ways that maintain efficiency of access, accuracy of data, as well as the ability to distribute the data. - Design of data structures for storing massive amounts of data that can be readily distributed over a network.