A performance comparison of distance-based query algorithms using R-trees in spatial databases

Efficient processing of distance-based queries (DBQs) is of great importance in spatial databases due to the wide area of applications that may address such queries. The most representative and known DBQs are the K Nearest Neighbors Query (KNNQ), q Distance Range Query (qDRQ), K Closest Pairs Query (KCPQ) and q Distance Join Query (qDJQ). In this paper, we propose new pruning mechanism to apply them in the design of new Recursive Best-First Search (RBFS) algorithms for DBQs between spatial objects indexed in R-trees. RBFS is a general search algorithm that runs in linear space and expands nodes in best-first order, but it can suffer from node re-expansion overhead (i.e. to expand nodes in best-first order, some nodes can be considered more than once). The R-tree and its variations are commonly cited spatial access methods that can be used for answering such spatial queries. Moreover, an exhaustive experimental study was also included using R-trees, which resulted to several conclus...

• Type: Journal
• Year: 2007
• Where: ISCI
• Authors: Antonio Corral, Jesús Manuel Almendros-Jiménez
• Keywords: Algorithm, ISCI 2007, Linear Space, Maximum Branching Factor