Name
Abstract | ||
|---|---|---|
Supporting high update throughput is important to provide real-time location information for many applications, which involve moving objects, such as security, military, and environmental monitoring. We present an R-tree-based index structure with a family of update strategies for supporting high update throughput. It groups updates in the update buffer, and bulk-applies them into the R-tree. Extensive empirical studies have shown that it outperforms existing techniques by 2-5 times. In our experimental environment, moreover, it is able to provide the real-time update capability, while its competitors fail to do so. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1016/j.ins.2012.03.001 | Inf. Sci. |
Keywords | Field | DocType |
r-tree-based index structure,real-time update capability,environmental monitoring,real-time location information,high update throughput,intensive application,update buffer,spatial indexing,extensive empirical study,update strategy,experimental environment,r tree,spatial index | Data mining,R-tree,Computer science,Search engine indexing,Artificial intelligence,Throughput,Machine learning,Empirical research,Spatial database,Environmental monitoring,Competitor analysis | Journal |
Volume | ISSN | Citations |
203, | 0020-0255 | 8 |
PageRank | References | Authors |
0.46 | 26 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| MoonBae Song | 1 | 123 | 18.05 |
| Hyunseung Choo | 2 | 1364 | 195.25 |
| Won Kim | 3 | 14 | 3.26 |