Article: Parallel cellular automata for large-scale urban simulation using load-balancing techniques

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TitleParallel cellular automata for large-scale urban simulation using load-balancing techniques
AuthorsLi, X2
Zhang, X1
Yeh, A1
Liu, X2
KeywordsCellular automata
GIS
Load-balancing
Parallel computing
Urban simulation
Issue Date2010
PublisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/13658816.asp
CitationInternational Journal Of Geographical Information Science, 2010, v. 24 n. 6, p. 803-820 [How to Cite?]
DOI: http://dx.doi.org/10.1080/13658810903107464
AbstractCellular automata (CA), which are a kind of bottom-up approaches, can be used to simulate urban dynamics and land use changes effectively. Urban simulation usually involves a large set of GIS data in terms of the extent of the study area and the number of spatial factors. The computation capability becomes a bottleneck of implementing CA for simulating large regions. Parallel computing techniques can be applied to CA for solving this kind of hard computation problem. This paper demonstrates that the performance of large-scale urban simulation can be significantly improved by using parallel computation techniques. The proposed urban CA is implemented in a parallel framework that runs on a cluster of PCs. A large region usually consists of heterogeneous or polarized development patterns. This study proposes a line-scanning method of load balance to reduce waiting time between parallel processors. This proposed method has been tested in a fast-growing region, the Pearl River Delta. The experiments indicate that parallel computation techniques with load balance can significantly improve the applicability of CA for simulating the urban development in this large complex region. © 2010 Taylor & Francis.
ISSN1365-8816
2011 Impact Factor: 1.472
2011 SCImago Journal Rankings: 0.077
DOIhttp://dx.doi.org/10.1080/13658810903107464
ISI Accession Number IDWOS:000276747400001
ReferencesReferences in Scopus
DC Field
Value
dc.contributor.authorLi, X
dc.contributor.authorZhang, X
dc.contributor.authorYeh, A
dc.contributor.authorLiu, X
dc.date.accessioned2010-10-31T13:36:20Z
dc.date.available2010-10-31T13:36:20Z
dc.date.issued2010
dc.description.abstractCellular automata (CA), which are a kind of bottom-up approaches, can be used to simulate urban dynamics and land use changes effectively. Urban simulation usually involves a large set of GIS data in terms of the extent of the study area and the number of spatial factors. The computation capability becomes a bottleneck of implementing CA for simulating large regions. Parallel computing techniques can be applied to CA for solving this kind of hard computation problem. This paper demonstrates that the performance of large-scale urban simulation can be significantly improved by using parallel computation techniques. The proposed urban CA is implemented in a parallel framework that runs on a cluster of PCs. A large region usually consists of heterogeneous or polarized development patterns. This study proposes a line-scanning method of load balance to reduce waiting time between parallel processors. This proposed method has been tested in a fast-growing region, the Pearl River Delta. The experiments indicate that parallel computation techniques with load balance can significantly improve the applicability of CA for simulating the urban development in this large complex region. © 2010 Taylor & Francis.
dc.description.natureLink_to_subscribed_fulltext
dc.identifier.citationInternational Journal Of Geographical Information Science, 2010, v. 24 n. 6, p. 803-820 [How to Cite?]
DOI: http://dx.doi.org/10.1080/13658810903107464
dc.identifier.citeulike10445698
dc.identifier.doihttp://dx.doi.org/10.1080/13658810903107464
dc.identifier.epage820
dc.identifier.hkuros182891
dc.identifier.isiWOS:000276747400001
dc.identifier.issn1365-8816
2011 Impact Factor: 1.472
2011 SCImago Journal Rankings: 0.077
dc.identifier.issue6
dc.identifier.openurl
dc.identifier.scopuseid_2-s2.0-77951196905
dc.identifier.spage803
dc.identifier.urihttp://hdl.handle.net/10722/127624
dc.identifier.volume24
dc.languageeng
dc.publisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/13658816.asp
dc.publisher.placeUnited Kingdom
dc.relation.ispartofInternational Journal of Geographical Information Science
dc.relation.referencesReferences in Scopus
dc.subjectCellular automata
dc.subjectGIS
dc.subjectLoad-balancing
dc.subjectParallel computing
dc.subjectUrban simulation
dc.titleParallel cellular automata for large-scale urban simulation using load-balancing techniques
dc.typeArticle
Author Affiliations
  1. The University of Hong Kong
  2. Sun Yat-Sen University