Title
iSky: Efficient and Progressive Skyline Computing in a Structured P2P Network
Abstract
An interesting problem in peer-based data management is efficient support for skyline queries within a multiattribute space. A skyline query retrieves from a set of multidimensional data points a subset of interesting points, compared to which no other points are better. Skyline queries play an important role in multi-criteria decision making and user preference applications. In this paper, we address the skyline computing problem in a structured P2P network. We exploit the iMinMax(θ) transformation to map high-dimensional data points to 1-dimensional values. All transformed data points are then distributed on a structured P2P network called BATON, where all peers are virtually organized as a balanced binary search tree. Subsequently, a progressive algorithm is proposed to compute skyline in the distributed P2P network. Further, we propose an adaptive skyline filtering technique to reduce both processing cost and communication cost during distributed skyline computing. Our performance study, with both synthetic and real datasets, shows that the proposed approach can dramatically reduce transferred data volume and gain quick response time.
Year
DOI
Venue
2008
10.1109/ICDCS.2008.40
ICDCS
Keywords
Field
DocType
multidimensional data point,skyline query retrieve,high-dimensional data point,structured p2p network,adaptive skyline,p2p network,skyline computing,data point,progressive skyline computing,skyline computing problem,skyline query,data volume,distributed computing,filtering,artificial neural networks,algorithm design and analysis,indexes,multidimensional systems,protocols,computer networks,high dimensional data,adaptive filters,binary search tree,data management,binary search trees,1 dimensional,information retrieval,baton,balanced binary search tree
Skyline,Data point,Data mining,Algorithm design,Computer science,Self-balancing binary search tree,Filter (signal processing),Exploit,Artificial neural network,Data management
Conference
ISSN
Citations 
PageRank 
1063-6927
24
0.72
References 
Authors
17
5
Name
Order
Citations
PageRank
Lijiang Chen130423.22
Bin Cui21843124.59
Hua Lu3138083.74
Linhao Xu4678.26
Quanqing Xu518912.04