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、检索和动态更新的优化方法。在其他应用中，空间数据通常用于描述地理和地理空间信息。这项研究将研究如何以最佳方式组织、分发和复制数据，以支持高效的可搜索性，从而提高数据可用性。这项研究是非常有必要的。现在存在着大量的空间数据，包括卫星(例如雷达卫星)图像、地理测绘、航空视频检查和天气观测，并不断收集新的空间数据。事实上，最近传感器技术的进步导致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跨网络环境中的几台主机进行托管，无论是本地还是远程。这带来了许多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，这些空间数据结构和算法具有尽可能少的存储空间，并且仍然允许有效地执行诸如节点添加和删除、节点锁定、范围查询等操作。-具有I/O意识的空间数据结构，对整个内存层次结构中不同的访问成本非常敏感，包括与分布式、远程和辅助存储的成本相关的问题。-分布式空间数据结构的缓存策略，以协调索引结构的分页，以便在用户请求发生变化时减少外部(网络或磁盘)访问。-分布式海量空间数据结构的一致性、复制性和可恢复性问题。-以保持获取效率、数据准确性以及分发数据的能力的方式管理和组织地理空间数据。-设计用于存储海量数据的数据结构，这些数据可以很容易地通过网络分发。

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.