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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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Detalles Bibliográficos
Autores principales: Zou, Zhiqiang, Wang, Yue, Cao, Kai, Qu, Tianshan, Wang, Zhongmin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Pergamon Press 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7125740/
https://www.ncbi.nlm.nih.gov/pubmed/32287505
http://dx.doi.org/10.1016/j.cageo.2013.04.019
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author Zou, Zhiqiang
Wang, Yue
Cao, Kai
Qu, Tianshan
Wang, Zhongmin
author_facet Zou, Zhiqiang
Wang, Yue
Cao, Kai
Qu, Tianshan
Wang, Zhongmin
author_sort Zou, Zhiqiang
collection PubMed
description 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.
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spelling pubmed-71257402020-04-08 Semantic overlay network for large-scale spatial information indexing Zou, Zhiqiang Wang, Yue Cao, Kai Qu, Tianshan Wang, Zhongmin Comput Geosci Article 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. Pergamon Press 2013-08 2013-04-27 /pmc/articles/PMC7125740/ /pubmed/32287505 http://dx.doi.org/10.1016/j.cageo.2013.04.019 Text en Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Zou, Zhiqiang
Wang, Yue
Cao, Kai
Qu, Tianshan
Wang, Zhongmin
Semantic overlay network for large-scale spatial information indexing
title Semantic overlay network for large-scale spatial information indexing
title_full Semantic overlay network for large-scale spatial information indexing
title_fullStr Semantic overlay network for large-scale spatial information indexing
title_full_unstemmed Semantic overlay network for large-scale spatial information indexing
title_short Semantic overlay network for large-scale spatial information indexing
title_sort semantic overlay network for large-scale spatial information indexing
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7125740/
https://www.ncbi.nlm.nih.gov/pubmed/32287505
http://dx.doi.org/10.1016/j.cageo.2013.04.019
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