Databases for Spatial Graph Management

用于空间图形管理的数据库对于包括交通、公用事业（例如天然气、电力）和城市管理在内的大量应用是非常重要的。该项目解决了物理数据库设计和查询处理领域的空间图形管理的需求。主要目标是开发，评估和实现一种新的空间图形存储和访问方法，称为连通性访问方法（CCAM），基于图形连接。 CCAM通过图分区方法将图的节点分配到磁盘页面，以最大化连接剩余比，即，一对连接的节点被分配给文件的公共页的机会。 另一个目标是开发可扩展的空间图聚类算法以及增量重组策略，以提高CCAM。 该项目还探讨了策略，以加强现有的几何访问方法管理连接属性沿着与邻近属性。在该项目中开发的技术进行了评估与基准图从先进的旅行者信息系统的应用

Databases for spatial graph management are very important for a large number of applications including transportation, utilities (e.g. gas, electricity) and urban management. This project addresses the needs of spatial graph management in the areas of physical database design and query processing. The main objective is to develop, evaluate and implement a novel spatial graph storage and access method, called Connectivity-Clustered Access Method (CCAM), based on graph-connectivity. CCAM assigns the nodes of a graphs to disk pages via the graph partitioning approach to maximize the Connectivity Residue Ratio, i.e., the chances that a pair of connected nodes are allocated to a common page of the file. Another objective is to develop scalable spatial graph-clustering algorithms as well as incremental reorganization strategies to enhance CCAM. This project also explores strategies to enhance existing geometric access methods for managing connectivity properties along with proximity properties. The techniques developed in the project are evaluated with benchmark graphs from Advanced Traveler Information System applications