VBI-Tree: A Peer-to-Peer Framework for Supporting Multi-Dimensional Indexing Schemes

Jagadish, H. V.; Ooi, Beng Chin; Vu, Quang Hieu; Zhang, Rong; Zhou, Aoying

doi:10.1109/icde.2006.169

Cited by 133 publications

(98 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A detailed discussion of this algorithm is provided in [13]. The efficiency of P-Grid in terms of ranges queries compared to related P2P systems such as [20,21] is also shown by performance evaluation studies such as [22] where P-Grid is among the best performing systems.…”

Section: Dhts For Index Managementmentioning

confidence: 99%

Scalable distributed indexing and query processing over Linked Data

Karnstedt

Sattler

Hauswirth

2012

Journal of Web Semantics

View full text Add to dashboard Cite

Section: Dhts For Index Managementmentioning

confidence: 99%

Scalable distributed indexing and query processing over Linked Data

Karnstedt

Sattler

Hauswirth

2012

Journal of Web Semantics

View full text Add to dashboard Cite

“…Complicated queries such as k-NN have to rely on multi-cast or additional indexes. Some locality-preserving data allocation approaches are also proposed, such as P-Grid [21] , P-Ring [22] , Baton [11] , Vbi-tree [10] , and Mercury [23] . The basic idea of these approaches is to keep data locality over the attribute as much as possible.…”

Section: Related Workmentioning

confidence: 99%

Continually Answering Constraint k-NN Queries in Unstructured P2P Systems

Wang

Yang

Wang

et al. 2008

J. Comput. Sci. Technol.

View full text Add to dashboard Cite

We consider the problem of efficiently computing distributed geographical k-NN queries in an unstructured peer-to-peer (P2P) system, in which each peer is managed by an individual organization and can only communicate with its logical neighboring peers. Such queries are based on local filter query statistics, and require as less communication cost as possible, which makes it more difficult than the existing distributed k-NN queries. Especially, we hope to reduce candidate peers and degrade communication cost. In this paper, we propose an efficient pruning technique to minimize the number of candidate peers to be processed to answer the k-NN queries. Our approach is especially suitable for continuous k-NN queries when updating peers, including changing ranges of peers, dynamically leaving or joining peers, and updating data in a peer. In addition, simulation results show that the proposed approach outperforms the existing Minimum Bounding Rectangle (MBR)-based query approaches, especially for continuous queries.

show abstract

“…Last but not least, R-trees are known to suffer in high dimensionality settings, which carries over to their decentralized counterparts. For example, the experiments in [11] showed that for dimensionality close to 20, this method was outperformed by the non-indexed approach of [15].…”

Section: Introductionmentioning

confidence: 99%

“…Being a binary tree, it allows for simple and efficient routing, in a manner reminiscent of Plaxton's algorithm [14] for single dimensional tree-like structures. Unlike other multidimensional index techniques, e.g., [11], peers in MIDAS only correspond to leaf nodes of the k-d tree. This, alleviates bottlenecks and increases scalability as no single peer is burdened with routing multiple requests.…”

Section: Introductionmentioning

confidence: 99%

“…The last category includes methods, e.g., [10], [11], that decentralize a conventional hierarchical multidimensional index, such as the R-tree. The basic idea is that each peer corresponds to a node (internal or leaf) of the index, and establishes link to its parent, children and selected nodes at the same depth of the tree but in different subtrees.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

MIDAS: Multi-attribute Indexing for Distributed Architecture Systems

Tsatsanifos

Sacharidis

Sellis

2011

Advances in Spatial and Temporal Databases

View full text Add to dashboard Cite

Abstract. This work presents a pure multidimensional, indexing infrastructure for large-scale decentralized networks that operate in extremely dynamic environments where peers join, leave and fail arbitrarily. We propose a new peer-to-peer variant implementing a virtual distributed k-d tree, and develop efficient algorithms for multidimensional point and range queries. Scalability is enhanced as each peer has only partial knowledge of the network. The most prominent feature of our method, is that in expectance each peer maintains O(log n) state and requests are resolved in O(log n) hops with respect to the overlay size n. In addition, we provide mechanisms for handling peer failures and improving fault tolerance as well as balancing the load of peers. Finally, our work is complemented by an experimental evaluation, where MIDAS is shown to outperform existing methods in spatial as well as in higher dimensional settings.

show abstract

VBI-Tree: A Peer-to-Peer Framework for Supporting Multi-Dimensional Indexing Schemes

Cited by 133 publications

References 16 publications

Scalable distributed indexing and query processing over Linked Data

Scalable distributed indexing and query processing over Linked Data

Continually Answering Constraint k-NN Queries in Unstructured P2P Systems

MIDAS: Multi-attribute Indexing for Distributed Architecture Systems

Contact Info

Product

Resources

About