On the Impact of Localization and Density Control Algorithms in Target Tracking Applications forWireless Sensor Networks
Target tracking is an important application of wireless sensor networks. The networks’ ability to locate and track an object is directed linked to the nodes’ ability to locate themselves. Consequently, localization systems are essential for target tracking applications. In addition, sensor networks...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2012-05-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/12/6/6930 |
| _version_ | 1828234008595529728 |
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| author | Joel J. P. C. Rodrigues Andre N. Campos Eduardo F. Nakamura Fabiola G. Nakamura Efren L. Souza |
| author_facet | Joel J. P. C. Rodrigues Andre N. Campos Eduardo F. Nakamura Fabiola G. Nakamura Efren L. Souza |
| author_sort | Joel J. P. C. Rodrigues |
| collection | DOAJ |
| description | Target tracking is an important application of wireless sensor networks. The networks’ ability to locate and track an object is directed linked to the nodes’ ability to locate themselves. Consequently, localization systems are essential for target tracking applications. In addition, sensor networks are often deployed in remote or hostile environments. Therefore, density control algorithms are used to increase network lifetime while maintaining its sensing capabilities. In this work, we analyze the impact of localization algorithms (RPE and DPE) and density control algorithms (GAF, A3 and OGDC) on target tracking applications. We adapt the density control algorithms to address the k-coverage problem. In addition, we analyze the impact of network density, residual integration with density control, and k-coverage on both target tracking accuracy and network lifetime. Our results show that DPE is a better choice for target tracking applications than RPE. Moreover, among the evaluated density control algorithms, OGDC is the best option among the three. Although the choice of the density control algorithm has little impact on the tracking precision, OGDC outperforms GAF and A3 in terms of tracking time. |
| first_indexed | 2024-04-12T19:48:22Z |
| format | Article |
| id | doaj.art-1e42ddbb9310483695cdaf0af2861603 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-12T19:48:22Z |
| publishDate | 2012-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-1e42ddbb9310483695cdaf0af28616032022-12-22T03:18:53ZengMDPI AGSensors1424-82202012-05-011266930695210.3390/s120606930On the Impact of Localization and Density Control Algorithms in Target Tracking Applications forWireless Sensor NetworksJoel J. P. C. RodriguesAndre N. CamposEduardo F. NakamuraFabiola G. NakamuraEfren L. SouzaTarget tracking is an important application of wireless sensor networks. The networks’ ability to locate and track an object is directed linked to the nodes’ ability to locate themselves. Consequently, localization systems are essential for target tracking applications. In addition, sensor networks are often deployed in remote or hostile environments. Therefore, density control algorithms are used to increase network lifetime while maintaining its sensing capabilities. In this work, we analyze the impact of localization algorithms (RPE and DPE) and density control algorithms (GAF, A3 and OGDC) on target tracking applications. We adapt the density control algorithms to address the k-coverage problem. In addition, we analyze the impact of network density, residual integration with density control, and k-coverage on both target tracking accuracy and network lifetime. Our results show that DPE is a better choice for target tracking applications than RPE. Moreover, among the evaluated density control algorithms, OGDC is the best option among the three. Although the choice of the density control algorithm has little impact on the tracking precision, OGDC outperforms GAF and A3 in terms of tracking time.http://www.mdpi.com/1424-8220/12/6/6930target trackingintegrated algorithmsdensity controllocalization |
| spellingShingle | Joel J. P. C. Rodrigues Andre N. Campos Eduardo F. Nakamura Fabiola G. Nakamura Efren L. Souza On the Impact of Localization and Density Control Algorithms in Target Tracking Applications forWireless Sensor Networks Sensors target tracking integrated algorithms density control localization |
| title | On the Impact of Localization and Density Control Algorithms in Target Tracking Applications forWireless Sensor Networks |
| title_full | On the Impact of Localization and Density Control Algorithms in Target Tracking Applications forWireless Sensor Networks |
| title_fullStr | On the Impact of Localization and Density Control Algorithms in Target Tracking Applications forWireless Sensor Networks |
| title_full_unstemmed | On the Impact of Localization and Density Control Algorithms in Target Tracking Applications forWireless Sensor Networks |
| title_short | On the Impact of Localization and Density Control Algorithms in Target Tracking Applications forWireless Sensor Networks |
| title_sort | on the impact of localization and density control algorithms in target tracking applications forwireless sensor networks |
| topic | target tracking integrated algorithms density control localization |
| url | http://www.mdpi.com/1424-8220/12/6/6930 |
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