Semantic overlay network for large-scale spatial information indexing

The increased demand for online services of spatial information poses new challenges to the combined filed of Computer Science and Geographic Information Science. Amongst others, these include fast indexing of spatial data in distributed networks. In this paper we propose a novel semantic overlay ne...

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Bibliographic Details
Main Authors: ZOU, Zhiqiang, WANG, Yue, CAO, Kai, QU, Tianshan, WANG, Zhongmin
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2013
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Online Access:https://ink.library.smu.edu.sg/sis_research/5410
https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=6413&context=sis_research
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Institution: Singapore Management University
Language: English
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Summary:The increased demand for online services of spatial information poses new challenges to the combined filed of Computer Science and Geographic Information Science. Amongst others, these include fast indexing of spatial data in distributed networks. In this paper we propose a novel semantic overlay network for large-scale multi-dimensional spatial information indexing, called SON_LSII, which has a hybrid structure integrating a semantic quad-tree and Chord ring. The SON_LSII is a small world overlay network that achieves a very competitive trade-off between indexing efficiency and maintenance overhead. To create SON_LSII, we use an effective semantic clustering strategy that considers two aspects, i.e., the semantic of spatial information that peer holds in overlay network and physical network performances. Based on SON_LSII, a mapping method is used to reduce the multi-dimensional features into a single dimension and an efficient indexing algorithm is presented to support complex range queries of the spatial information with a massive number of concurrent users. The results from extensive experiments demonstrate that SON_LSII is superior to existing overlay networks in various respects, including scalability, maintenance, rate of indexing hits, indexing logical hops, and adaptability. Thus, the proposed SON_LSII can be used for large-scale spatial information indexing.