Analysing Probabilistic Support Vector Machine Based Localization In Wireless Sensor Networks
Localizing sensors in a sensor network is one of the severe bottlenecks that must be dealt with, before exploiting these kinds of networks efficiently. While there has been many techniques and methods proposed for the issue, most of them suffer from low accuracy, or impose extra costs to the network...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Iran Telecom Research Center
2011-06-01
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| Series: | International Journal of Information and Communication Technology Research |
| Subjects: | |
| Online Access: | http://ijict.itrc.ac.ir/article-1-216-en.html |
| _version_ | 1828039408264151040 |
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| author | Reza Samadian Seyed Majid Noorhoseini |
| author_facet | Reza Samadian Seyed Majid Noorhoseini |
| author_sort | Reza Samadian |
| collection | DOAJ |
| description | Localizing sensors in a sensor network is one of the severe bottlenecks that must be dealt with, before exploiting these kinds of networks efficiently. While there has been many techniques and methods proposed for the issue, most of them suffer from low accuracy, or impose extra costs to the network. A Support Vector Machine (SVM) based method has already been proposed which uses machine learning techniques to achieve a fairly accurate estimate of the location of the nodes. In this paper, we propose to use probabilistic SVM, which is more powerful than the existing method. Moreover, an innovative post processing step called ARPoFiL will be proposed that provides even more improvement to the accuracy of the location of the sensor nodes. We will show analytically and experimentally that probabilistic SVM integrated with ARPoFiL completely outperforms the existing method, particularly in sparse networks and rough environments with lots of coverage holes. |
| first_indexed | 2024-04-10T16:41:36Z |
| format | Article |
| id | doaj.art-e6a307a5435b47398db500702c557171 |
| institution | Directory Open Access Journal |
| issn | 2251-6107 2783-4425 |
| language | English |
| last_indexed | 2024-04-10T16:41:36Z |
| publishDate | 2011-06-01 |
| publisher | Iran Telecom Research Center |
| record_format | Article |
| series | International Journal of Information and Communication Technology Research |
| spelling | doaj.art-e6a307a5435b47398db500702c5571712023-02-08T07:30:24ZengIran Telecom Research CenterInternational Journal of Information and Communication Technology Research2251-61072783-44252011-06-01324756Analysing Probabilistic Support Vector Machine Based Localization In Wireless Sensor NetworksReza Samadian0Seyed Majid Noorhoseini1 Localizing sensors in a sensor network is one of the severe bottlenecks that must be dealt with, before exploiting these kinds of networks efficiently. While there has been many techniques and methods proposed for the issue, most of them suffer from low accuracy, or impose extra costs to the network. A Support Vector Machine (SVM) based method has already been proposed which uses machine learning techniques to achieve a fairly accurate estimate of the location of the nodes. In this paper, we propose to use probabilistic SVM, which is more powerful than the existing method. Moreover, an innovative post processing step called ARPoFiL will be proposed that provides even more improvement to the accuracy of the location of the sensor nodes. We will show analytically and experimentally that probabilistic SVM integrated with ARPoFiL completely outperforms the existing method, particularly in sparse networks and rough environments with lots of coverage holes.http://ijict.itrc.ac.ir/article-1-216-en.htmlcomponentwireless sensor networks (wsn)support vector machine (svm)localizationprobabilistic svmartificial neural networks (ann) |
| spellingShingle | Reza Samadian Seyed Majid Noorhoseini Analysing Probabilistic Support Vector Machine Based Localization In Wireless Sensor Networks International Journal of Information and Communication Technology Research component wireless sensor networks (wsn) support vector machine (svm) localization probabilistic svm artificial neural networks (ann) |
| title | Analysing Probabilistic Support Vector Machine Based Localization In Wireless Sensor Networks |
| title_full | Analysing Probabilistic Support Vector Machine Based Localization In Wireless Sensor Networks |
| title_fullStr | Analysing Probabilistic Support Vector Machine Based Localization In Wireless Sensor Networks |
| title_full_unstemmed | Analysing Probabilistic Support Vector Machine Based Localization In Wireless Sensor Networks |
| title_short | Analysing Probabilistic Support Vector Machine Based Localization In Wireless Sensor Networks |
| title_sort | analysing probabilistic support vector machine based localization in wireless sensor networks |
| topic | component wireless sensor networks (wsn) support vector machine (svm) localization probabilistic svm artificial neural networks (ann) |
| url | http://ijict.itrc.ac.ir/article-1-216-en.html |
| work_keys_str_mv | AT rezasamadian analysingprobabilisticsupportvectormachinebasedlocalizationinwirelesssensornetworks AT seyedmajidnoorhoseini analysingprobabilisticsupportvectormachinebasedlocalizationinwirelesssensornetworks |