Welcome to D
SIGMOD 2004
PODS 2004
SIGMOD RECOR
CIKM 2004
DASFAA 2004
DBPL 2003
DE-BULLETIN
DEBS 2004
DMKD 2004
DMSN 2004
DOLAP 2004
DPDJ 2004
EDBT 2004
ER 2003
GIS 2004
HDP 2004
HYPERTEXT 20
ICDE 2004
ICDT 2003
JCDL 2004
MDM
<<< = MDM'03 Paper>>>
 = MDM'04 Paper
MIR 2004
MIS 2004
MMDB 2004
MOBIDE 2003
RIDE 2004
SBBD 2003
SIGIR FORUM
SIGIR 2004
SIGKDD EXPLO
SIGKDD 2004
SSDBM 2004
SSTD 2003
TIME 2004
TODS 2004
VLDB 2004
VLDB Journal
WEBDB 2004
WIDM 2004
XIME-P 2004
Footer

Adaptive Location Management in Mobile Environments


Ratul kr. Majumdar, Krithi Ramamritham, and Ming Xiong

  View Paper (PDF)  

Return to Location-Aware Services


Abstract

Location management in mobile environments consists of two major operations: location update and paging. The more up-to-date the location information, the less paging becomes necessary and vice versa. The conventional approach is the location area based approach (LA-based approach), where a location area (LA) consists of multiple cells. When the mobile station (MS) enters a new location area, the MS immediately updates its location information at the new location's visitor location register (VLR) and this update is propagated to the MS's home location register (HLR). The major drawback of the LA-based approach is that it does not consider any mobility patterns, or call arrival patterns. Moreover, MS updates frequently when it roams only within the boundary cells of different location areas, resulting in unnecessary location updates. So, there is a need for an efficient algorithm which can eliminate the drawbacks of the LA-based approach. To this end, an adaptive location management algorithm is described in this paper: an MS dynamically determines whether or not to update when it moves to a new LA, so that each location update becomes a necessary location update, i.e., in each updated location area at least one call is made. We have conducted experiments to capture the effect of mobility and call arrival patterns on the new location update strategy. We have also tested our algorithm with SUMATRA (Stanford University Mobile Activity TRAces), which has been validated against real data on call and mobility traces. Experimental results show that our adaptive location management algorithm considerably reduces the location management cost, by avoiding unnecessary location updates.

BIBTEX


@inproceedings       {DBLP:conf/mdm/MajumdarRX03,    author    = {Ratul kr. Majumdar and
                Krithi Ramamritham and
                Ming Xiong},
   booktitle = {Mobile Data Management},
   title     = {Adaptive Location Management in Mobile Environments.},
   pages     = {196-211},
   year      = {2003},
   url       = {db/conf/mdm/mdm2003.html#MajumdarRX03},
   ee        = {http://link.springer.de/link/service/series/0558/bibs/2574/25740196.htm},
   crossref  = {conf/mdm/2003},
   bibsource = {DBLP, http://dblp.uni-trier.de}  
}



©2005 Association for Computing Machinery