Uncertainty-Aware Sensor Deployment Strategy in Mixed Wireless Sensor Networks
Deployment is a fundamental issue in wireless sensor networks (WSNs), which affects the performance and lifetime of the networks. Usually the sensor locations are precomputed based on “perfect” sensor detection model, whereas sensors may not always provide reliable information, either due to operati...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2013-11-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2013/834704 |
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| _version_ | 1832547879997145088 |
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| author | Yan Chang Shukui Zhang Yang Zhang Jianxi Fan Jin Wang |
| author_facet | Yan Chang Shukui Zhang Yang Zhang Jianxi Fan Jin Wang |
| author_sort | Yan Chang |
| collection | DOAJ |
| description | Deployment is a fundamental issue in wireless sensor networks (WSNs), which affects the performance and lifetime of the networks. Usually the sensor locations are precomputed based on “perfect” sensor detection model, whereas sensors may not always provide reliable information, either due to operational tolerance levels or environmental factors. Therefore, it is very important to take into account this uncertainty in the deployment process. In this paper, we address the problem of sensor deployment in a mixed sensor network where the mobile and static nodes work collaboratively to perform deployment optimization task. We consider the Gaussian white noise in the environment and present a centralized algorithm (FABGM for short) which discoveres vacancies by using detection model based on false alarm and moves the mobile nodes according to the method based on bipartite graph matching in this study. In this algorithm, the management node of the WSNs collects the geographical information of all of the static and mobile sensors. Then, the management node executes the algorithm to get the best matches between mobile sensors and coverage holes. Simulation results are presented to demonstrate the effectiveness of the proposed approach. |
| format | Article |
| id | doaj-art-da2d588ca8c0482a91ecd19cc3410b2d |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2013-11-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-da2d588ca8c0482a91ecd19cc3410b2d2025-02-03T06:43:05ZengWileyInternational Journal of Distributed Sensor Networks1550-14772013-11-01910.1155/2013/834704Uncertainty-Aware Sensor Deployment Strategy in Mixed Wireless Sensor NetworksYan Chang0Shukui Zhang1Yang Zhang2Jianxi Fan3Jin Wang4 School of Computer Science and Technology, Soochow University, Suzhou 215006, China State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210093, China School of Engineering, University of Glasgow, Glasgow, G12 8QQ, UK School of Computer Science and Technology, Soochow University, Suzhou 215006, China School of Computer Science and Technology, Soochow University, Suzhou 215006, ChinaDeployment is a fundamental issue in wireless sensor networks (WSNs), which affects the performance and lifetime of the networks. Usually the sensor locations are precomputed based on “perfect” sensor detection model, whereas sensors may not always provide reliable information, either due to operational tolerance levels or environmental factors. Therefore, it is very important to take into account this uncertainty in the deployment process. In this paper, we address the problem of sensor deployment in a mixed sensor network where the mobile and static nodes work collaboratively to perform deployment optimization task. We consider the Gaussian white noise in the environment and present a centralized algorithm (FABGM for short) which discoveres vacancies by using detection model based on false alarm and moves the mobile nodes according to the method based on bipartite graph matching in this study. In this algorithm, the management node of the WSNs collects the geographical information of all of the static and mobile sensors. Then, the management node executes the algorithm to get the best matches between mobile sensors and coverage holes. Simulation results are presented to demonstrate the effectiveness of the proposed approach.https://doi.org/10.1155/2013/834704 |
| spellingShingle | Yan Chang Shukui Zhang Yang Zhang Jianxi Fan Jin Wang Uncertainty-Aware Sensor Deployment Strategy in Mixed Wireless Sensor Networks International Journal of Distributed Sensor Networks |
| title | Uncertainty-Aware Sensor Deployment Strategy in Mixed Wireless Sensor Networks |
| title_full | Uncertainty-Aware Sensor Deployment Strategy in Mixed Wireless Sensor Networks |
| title_fullStr | Uncertainty-Aware Sensor Deployment Strategy in Mixed Wireless Sensor Networks |
| title_full_unstemmed | Uncertainty-Aware Sensor Deployment Strategy in Mixed Wireless Sensor Networks |
| title_short | Uncertainty-Aware Sensor Deployment Strategy in Mixed Wireless Sensor Networks |
| title_sort | uncertainty aware sensor deployment strategy in mixed wireless sensor networks |
| url | https://doi.org/10.1155/2013/834704 |
| work_keys_str_mv | AT yanchang uncertaintyawaresensordeploymentstrategyinmixedwirelesssensornetworks AT shukuizhang uncertaintyawaresensordeploymentstrategyinmixedwirelesssensornetworks AT yangzhang uncertaintyawaresensordeploymentstrategyinmixedwirelesssensornetworks AT jianxifan uncertaintyawaresensordeploymentstrategyinmixedwirelesssensornetworks AT jinwang uncertaintyawaresensordeploymentstrategyinmixedwirelesssensornetworks |