RSS-Based Coverage Deployment Method Under Probability Model in 3D-WSN
Due to the wider application of wireless sensor networks in real life, 3D coverage closer to the actual application environment has become a research hotspot of current sensor networks. To this end, this paper proposes a three-dimensional coverage deployment method based on RSS (Received Signal Stre...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8935224/ |
| _version_ | 1830300788483686400 |
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| author | Zhanjun Hao Nanjiang Qu Xiaochao Dang Jiaojiao Hou |
| author_facet | Zhanjun Hao Nanjiang Qu Xiaochao Dang Jiaojiao Hou |
| author_sort | Zhanjun Hao |
| collection | DOAJ |
| description | Due to the wider application of wireless sensor networks in real life, 3D coverage closer to the actual application environment has become a research hotspot of current sensor networks. To this end, this paper proposes a three-dimensional coverage deployment method based on RSS (Received Signal Strength) under a probabilistic model. According to the path loss of the wireless signal in the propagation process, the distance between the nodes can be roughly calculated, and the maximum distance between the nodes is defined by setting a threshold of the path loss, thereby further ensuring network connectivity and network quality. The probability coverage model is used and the cube-based network coverage is constructed. Based on this, the optimal coverage deployment problem in 3D-WSN is explored. Combining and improving the traditional particle swarm optimization algorithm can converge faster and avoid falling into local optimum. The simulation results show that the proposed method can converge quickly to improve network coverage and effectively reduce network energy consumption. In addition, we built a real experimental environment to verify the network quality by observing the RSSI (Received Signal Strength Indicator) changes. The experimental results verify the effectiveness of the proposed method. |
| first_indexed | 2024-12-19T08:34:31Z |
| format | Article |
| id | doaj.art-347c152170d54eecb5ef59a7f5892b3c |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T08:34:31Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-347c152170d54eecb5ef59a7f5892b3c2022-12-21T20:29:04ZengIEEEIEEE Access2169-35362019-01-01718309118310410.1109/ACCESS.2019.29602998935224RSS-Based Coverage Deployment Method Under Probability Model in 3D-WSNZhanjun Hao0https://orcid.org/0000-0002-9740-0988Nanjiang Qu1https://orcid.org/0000-0002-5251-3989Xiaochao Dang2https://orcid.org/0000-0002-9655-0044Jiaojiao Hou3https://orcid.org/0000-0002-9440-9557College of Computer Science and Engineering, Northwest Normal University, Lanzhou, ChinaCollege of Computer Science and Engineering, Northwest Normal University, Lanzhou, ChinaCollege of Computer Science and Engineering, Northwest Normal University, Lanzhou, ChinaCollege of Computer Science and Engineering, Northwest Normal University, Lanzhou, ChinaDue to the wider application of wireless sensor networks in real life, 3D coverage closer to the actual application environment has become a research hotspot of current sensor networks. To this end, this paper proposes a three-dimensional coverage deployment method based on RSS (Received Signal Strength) under a probabilistic model. According to the path loss of the wireless signal in the propagation process, the distance between the nodes can be roughly calculated, and the maximum distance between the nodes is defined by setting a threshold of the path loss, thereby further ensuring network connectivity and network quality. The probability coverage model is used and the cube-based network coverage is constructed. Based on this, the optimal coverage deployment problem in 3D-WSN is explored. Combining and improving the traditional particle swarm optimization algorithm can converge faster and avoid falling into local optimum. The simulation results show that the proposed method can converge quickly to improve network coverage and effectively reduce network energy consumption. In addition, we built a real experimental environment to verify the network quality by observing the RSSI (Received Signal Strength Indicator) changes. The experimental results verify the effectiveness of the proposed method.https://ieeexplore.ieee.org/document/8935224/Three-dimensional coverageprobability modelRSSnetwork coveragenetwork quality |
| spellingShingle | Zhanjun Hao Nanjiang Qu Xiaochao Dang Jiaojiao Hou RSS-Based Coverage Deployment Method Under Probability Model in 3D-WSN IEEE Access Three-dimensional coverage probability model RSS network coverage network quality |
| title | RSS-Based Coverage Deployment Method Under Probability Model in 3D-WSN |
| title_full | RSS-Based Coverage Deployment Method Under Probability Model in 3D-WSN |
| title_fullStr | RSS-Based Coverage Deployment Method Under Probability Model in 3D-WSN |
| title_full_unstemmed | RSS-Based Coverage Deployment Method Under Probability Model in 3D-WSN |
| title_short | RSS-Based Coverage Deployment Method Under Probability Model in 3D-WSN |
| title_sort | rss based coverage deployment method under probability model in 3d wsn |
| topic | Three-dimensional coverage probability model RSS network coverage network quality |
| url | https://ieeexplore.ieee.org/document/8935224/ |
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