Paper Info
Title
An index structure for parallel processing of multidimensional data
Abstract
Generally, multidimensional data require a large amount of storage space. There are a few limits to store and manage those large amounts of data in single workstation. If we manage the data on parallel computing environment which is being actively researched these days, we can get highly improved performance. In this paper, we propose an efficient index structure for multidimensional data that exploits the parallel computing environment. The proposed index structure is constructed based on nP(processor)-n×mD(disk) architecture which is the hybrid type of nP-nD and 1P-nD. Its node structure increases fan-out and reduces the height of an index tree. Our proposed index structure gives a range search algorithm that maximizes I/O parallelism. The range search algorithm is applied to k-nearest neighbor queries. Through various experiments, it is shown that the proposed method outperforms other parallel index structures.
Year
DOI
Venue
2005
10.1007/11563952_51
WAIM
Keywords
Field
DocType
parallel computer,k nearest neighbor,parallel processing,indexation,search algorithm,weed management
Data structure,Data mining,Data processing,Search algorithm,Parallel algorithm,Computer science,Tree (data structure),Range query (data structures),Workstation,Online analytical processing
Conference
ISBN
Citations 
PageRank 
3-540-29227-6
4
0.39
References 
Authors
16
5
Name
Order
Citations
PageRank
Kyoungsoo Bok15516.55
Dongmin Seo24910.64
Seok Il Song3243.62
Myoung Ho Kim41040273.40
Jaesoo Yoo512335.63