Name
Abstract | ||
|---|---|---|
There is rapidly increasing interest in Location Based Service(LBS) which utilizes location data of moving objects. To efficiently manage the huge amounts of location data in LBS, the GALIS (Gracefully Aging Location Information System) architecture, a cluster-based distributed computing architecture, is proposed. The GALIS using the non-uniform 2-level grid algorithm performs load balancing and indexing for nodes. However, the non-uniform 2-level grid algorithm has a problem creating unnecessary nodes when moving objects are crowded in a certain area. Therefore, a new node split algorithm, which is more efficient for various distribution of moving objects, is proposed in this paper. Because the algorithm proposed in this paper considers spatial distribution for the current location of moving objects, it can perform efficient load balancing without creating unnecessary nodes even when moving objects are congested in a certain area. Besides, the various data distribution configuration for moving objects has been experimented by implementing node split simulators and it's been verified that the proposed algorithm splits nodes more efficiently than the existing algorithm. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11745693_37 | GPC |
Keywords | Field | DocType |
spatial distribution,certain area,existing algorithm,2-level grid algorithm,location data,grid-based node split algorithm,current location data,various data distribution configuration,new node split algorithm,current location,proposed algorithm,unnecessary node,indexation,location based service,information system,load balance,distributed computing | Mobile computing,Load balancing (computing),Computer science,Search engine indexing,Algorithm,Location-based service,Systems architecture,Ubiquitous computing,Computer cluster,Grid,Distributed computing | Conference |
Volume | ISSN | ISBN |
3947 | 0302-9743 | 3-540-33809-8 |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jae-Kwan Yun | 1 | 16 | 4.32 |
| Seungwon Lee | 2 | 127 | 32.51 |
| Dong-Suk Hong | 3 | 10 | 3.67 |
| Dong-Oh Kim | 4 | 15 | 6.72 |
| Ki-Joon Han | 5 | 26 | 6.76 |