Paper Info
Title
Using compressed index structures for processing moving objects in large spatio-temporal databases
Abstract
This paper develops a novel, compressed B^+-tree based indexing scheme that supports the processing of moving objects in one-, two-, and multi- dimensional spaces. The past, current, and anticipated future trajectories of movements are fully indexed and well organized. No parameterized functions and geometric representations are introduced in our data model so that update operations are not required and the maintenance of index structures can be accomplished by basic insertion and deletion operations. The proposed method has two contributions. First, the spatial and temporal attributes of trajectories are accurately preserved and well organized into compact index structures with very efficient memory space utilization and storage requirement. Second, index maintenance overheads are more economical and query performance is more responsive than those of conventional methods. Both analytical and empirical studies show that our proposed indexing scheme outperforms the TPR-tree.
Year
DOI
Venue
2012
10.1016/j.jss.2011.08.005
Journal of Systems and Software
Keywords
Field
DocType
compact index structure,conventional method,basic insertion,large spatio-temporal databases,anticipated future trajectory,proposed indexing scheme,index maintenance overhead,index structure,data model,indexing scheme
Data mining,Parameterized complexity,Computer science,Search engine indexing,Theoretical computer science,Temporal database,Data model,Empirical research,Overhead (business)
Journal
Volume
Issue
ISSN
85
1
0164-1212
Citations 
PageRank 
References 
3
0.40
25
Authors
1
Name
Order
Citations
PageRank
Hung-Yi Lin1398.74