Predictive Trajectory-Based Mobile Data Gathering Scheme for Wireless Sensor Networks
Tradition wireless sensor networks (WSNs) transmit data by single or multiple hops. However, some sensor nodes (SNs) close to a static base station forward data more frequently than others, which results in the problem of energy holes and makes networks fragile. One promising solution is to use a mo...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/3941074 |
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| _version_ | 1832566452460191744 |
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| author | Fan Chao Zhiqin He Renkuan Feng Xiao Wang Xiangping Chen Changqi Li Ying Yang |
| author_facet | Fan Chao Zhiqin He Renkuan Feng Xiao Wang Xiangping Chen Changqi Li Ying Yang |
| author_sort | Fan Chao |
| collection | DOAJ |
| description | Tradition wireless sensor networks (WSNs) transmit data by single or multiple hops. However, some sensor nodes (SNs) close to a static base station forward data more frequently than others, which results in the problem of energy holes and makes networks fragile. One promising solution is to use a mobile node as a mobile sink (MS), which is especially useful in energy-constrained networks. In these applications, the tour planning of MS is a key to guarantee the network performance. In this paper, a novel strategy is proposed to reduce the latency of mobile data gathering in a WSN while the routing strategies and tour planning of MS are jointly optimized. First, the issue of network coverage is discussed before the appropriate number of clusters being calculated. A dynamic clustering scheme is then developed where a virtual cluster center is defined as the MS sojourn for data collection. Afterwards, a tour planning of MS based on prediction is proposed subject to minimizing the traveling distance to collect data. The proposed method is simulated in a MATLAB platform to show the overall performance of the developed system. Furthermore, the physical tests on a test rig are also carried out where a small WSN based on an unmanned aerial vehicle (UAV) is developed in our laboratory. The test results validate the feasibility and effectiveness of the method proposed. |
| format | Article |
| id | doaj-art-00f66deb44ab4f3a89e1dc51d1e8cf0e |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-00f66deb44ab4f3a89e1dc51d1e8cf0e2025-02-03T01:03:58ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/39410743941074Predictive Trajectory-Based Mobile Data Gathering Scheme for Wireless Sensor NetworksFan Chao0Zhiqin He1Renkuan Feng2Xiao Wang3Xiangping Chen4Changqi Li5Ying Yang6School of Electrical Engineering Guizhou University, Guiyang 550025, ChinaSchool of Electrical Engineering Guizhou University, Guiyang 550025, ChinaSchool of Electrical Engineering Guizhou University, Guiyang 550025, ChinaSchool of Electrical Engineering Guizhou University, Guiyang 550025, ChinaSchool of Electrical Engineering Guizhou University, Guiyang 550025, ChinaSchool of Electrical Engineering Guizhou University, Guiyang 550025, ChinaSchool of Electrical Engineering Guizhou University, Guiyang 550025, ChinaTradition wireless sensor networks (WSNs) transmit data by single or multiple hops. However, some sensor nodes (SNs) close to a static base station forward data more frequently than others, which results in the problem of energy holes and makes networks fragile. One promising solution is to use a mobile node as a mobile sink (MS), which is especially useful in energy-constrained networks. In these applications, the tour planning of MS is a key to guarantee the network performance. In this paper, a novel strategy is proposed to reduce the latency of mobile data gathering in a WSN while the routing strategies and tour planning of MS are jointly optimized. First, the issue of network coverage is discussed before the appropriate number of clusters being calculated. A dynamic clustering scheme is then developed where a virtual cluster center is defined as the MS sojourn for data collection. Afterwards, a tour planning of MS based on prediction is proposed subject to minimizing the traveling distance to collect data. The proposed method is simulated in a MATLAB platform to show the overall performance of the developed system. Furthermore, the physical tests on a test rig are also carried out where a small WSN based on an unmanned aerial vehicle (UAV) is developed in our laboratory. The test results validate the feasibility and effectiveness of the method proposed.http://dx.doi.org/10.1155/2021/3941074 |
| spellingShingle | Fan Chao Zhiqin He Renkuan Feng Xiao Wang Xiangping Chen Changqi Li Ying Yang Predictive Trajectory-Based Mobile Data Gathering Scheme for Wireless Sensor Networks Complexity |
| title | Predictive Trajectory-Based Mobile Data Gathering Scheme for Wireless Sensor Networks |
| title_full | Predictive Trajectory-Based Mobile Data Gathering Scheme for Wireless Sensor Networks |
| title_fullStr | Predictive Trajectory-Based Mobile Data Gathering Scheme for Wireless Sensor Networks |
| title_full_unstemmed | Predictive Trajectory-Based Mobile Data Gathering Scheme for Wireless Sensor Networks |
| title_short | Predictive Trajectory-Based Mobile Data Gathering Scheme for Wireless Sensor Networks |
| title_sort | predictive trajectory based mobile data gathering scheme for wireless sensor networks |
| url | http://dx.doi.org/10.1155/2021/3941074 |
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