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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Pergamon Press
2013
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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 |
_version_ | 1783516008171962368 |
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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. |
format | Online Article Text |
id | pubmed-7125740 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Pergamon Press |
record_format | MEDLINE/PubMed |
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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