Name
Abstract | ||
|---|---|---|
With the continued advancements in location-based services involved infrastructures, large amount of time-based location data are quickly accumulated. Distributed processing techniques on such large trajectory data sets are urgently needed. We propose TRUSTER: a distributed trajectory data processing system on clusters. TRUSTER employs a distributed indexing method on large scale trajectory data sets, and it makes spatio-temporal queries execute efficiently on clusters. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-00887-0_69 | DASFAA |
Keywords | Field | DocType |
location-based service,indexing method,time-based location data,large trajectory data set,trajectory data processing,continued advancement,large amount,spatio-temporal query,trajectory data,large scale trajectory data,data processing | Data mining,Cluster (physics),Data processing,Data set,Computer science,Data processing system,Search engine indexing,Location data,Trajectory,Database,Distributed computing | Conference |
Volume | ISSN | Citations |
5463 | 0302-9743 | 16 |
PageRank | References | Authors |
0.70 | 5 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bin Yang | 1 | 706 | 34.93 |
| Qiang Ma | 2 | 295 | 36.71 |
| Weining Qian | 3 | 1064 | 81.09 |
| Aoying Zhou | 4 | 2632 | 238.85 |