A site selection method of DNS using the particle swarm optimization algorithm
© 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...
| Main Authors: | , , , , , , , |
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| Format: | Journal Article |
| Published: |
Blackwell Publishers
2017
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| Online Access: | http://hdl.handle.net/20.500.11937/58064 |
| _version_ | 1848760168558362624 |
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| author | Liao, Y. Chen, W. Wu, K. Li, D. Liu, Xin Geng, G. Su, Z. Zheng, Z. |
| author_facet | Liao, Y. Chen, W. Wu, K. Li, D. Liu, Xin Geng, G. Su, Z. Zheng, Z. |
| author_sort | Liao, Y. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | © 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. |
| first_indexed | 2025-11-14T10:11:29Z |
| format | Journal Article |
| id | curtin-20.500.11937-58064 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T10:11:29Z |
| publishDate | 2017 |
| publisher | Blackwell Publishers |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-580642017-11-20T08:58:17Z A site selection method of DNS using the particle swarm optimization algorithm Liao, Y. Chen, W. Wu, K. Li, D. Liu, Xin Geng, G. Su, Z. Zheng, Z. © 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. 2017 Journal Article http://hdl.handle.net/20.500.11937/58064 10.1111/tgis.12244 Blackwell Publishers restricted |
| spellingShingle | Liao, Y. Chen, W. Wu, K. Li, D. Liu, Xin Geng, G. Su, Z. Zheng, Z. A site selection method of DNS using the particle swarm optimization algorithm |
| title | A site selection method of DNS using the particle swarm optimization algorithm |
| title_full | A site selection method of DNS using the particle swarm optimization algorithm |
| title_fullStr | A site selection method of DNS using the particle swarm optimization algorithm |
| title_full_unstemmed | A site selection method of DNS using the particle swarm optimization algorithm |
| title_short | A site selection method of DNS using the particle swarm optimization algorithm |
| title_sort | site selection method of dns using the particle swarm optimization algorithm |
| url | http://hdl.handle.net/20.500.11937/58064 |