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dc.contributor.authorLiao, Y.
dc.contributor.authorChen, W.
dc.contributor.authorWu, K.
dc.contributor.authorLi, D.
dc.contributor.authorLiu, Xin
dc.contributor.authorGeng, G.
dc.contributor.authorSu, Z.
dc.contributor.authorZheng, Z.
dc.date.accessioned2017-11-20T08:50:09Z
dc.date.available2017-11-20T08:50:09Z
dc.date.created2017-11-20T08:13:29Z
dc.date.issued2017
dc.identifier.citationLiao, Y. and Chen, W. and Wu, K. and Li, D. and Liu, X. and Geng, G. and Su, Z. et al. 2017. A site selection method of DNS using the particle swarm optimization algorithm. Transactions in GIS. 21 (5): pp. 969-983.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/58064
dc.identifier.doi10.1111/tgis.12244
dc.description.abstract

© 2016 John Wiley & Sons Ltd The Domain Name System (DNS) is an essential component of the functionality of the Internet. With the growing number of domain names and Internet users, the growing rate and number of visit quantity and analytic capacity of DNS are also proportional to the Internet users' size. This study (based on the analysis of access popularity and the distribution of massive DNS log data) aims to optimize the configuration of the DNS sites, which has become an important problem. The ArcGIS software is used to show the temporal and spatial distributions of visit source of DNS logs. This study also analyzes the influence of different sites and the dependence on DNS service in different regions of the world. This information is important to further decision-making on new DNS site selection. This article proposes new DNS site selection solutions, using particle swarm and multi-objective particle swarm optimization algorithms for one new site and multiple sites, respectively. The results from particle swarm optimization, genetic, and simulated annealing algorithms were compared and experimental results confirmed the correctness and effectiveness of the proposed methods. The proposed methods could also be extended to solve other layout related issues, such as onsite facility layout and road network optimization.

dc.publisherBlackwell Publishers
dc.titleA site selection method of DNS using the particle swarm optimization algorithm
dc.typeJournal Article
dcterms.source.volume21
dcterms.source.number5
dcterms.source.startPage969
dcterms.source.endPage983
dcterms.source.issn1361-1682
dcterms.source.titleTransactions in GIS
curtin.departmentSustainability Policy Institute
curtin.accessStatusFulltext not available


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