Distributed and morphological operation-based data collection algorithm
When monitoring the environment with wireless sensor networks, the data sensed by the nodes within event backbone regions can adequately represent the events. As a result, identifying event backbone regions is a key issue for wireless sensor networks. With this aim, we propose a distributed and morp...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2017-07-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147717717593 |
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| _version_ | 1850106466637185024 |
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| author | Yalin Nie Haijun Wang Yujie Qin Zeyu Sun |
| author_facet | Yalin Nie Haijun Wang Yujie Qin Zeyu Sun |
| author_sort | Yalin Nie |
| collection | DOAJ |
| description | When monitoring the environment with wireless sensor networks, the data sensed by the nodes within event backbone regions can adequately represent the events. As a result, identifying event backbone regions is a key issue for wireless sensor networks. With this aim, we propose a distributed and morphological operation-based data collection algorithm. Inspired by the use of morphological erosion and dilation on binary images, the proposed distributed and morphological operation-based data collection algorithm calculates the structuring neighbors of each node based on the structuring element, and it produces an event-monitoring map of structuring neighbors with less cost and then determines whether to erode or not. The remaining nodes that are not eroded become the event backbone nodes and send their sensing data. Moreover, according to the event backbone regions, the sink can approximately recover the complete event regions by the dilation operation. The algorithm analysis and experimental results show that the proposed algorithm can lead to lower overhead, decrease the amount of transmitted data, prolong the network lifetime, and rapidly recover event regions. |
| format | Article |
| id | doaj-art-2c4ea7542b124b2593d28b7b44eeb32f |
| institution | OA Journals |
| issn | 1550-1477 |
| language | English |
| publishDate | 2017-07-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-2c4ea7542b124b2593d28b7b44eeb32f2025-08-20T02:38:49ZengWileyInternational Journal of Distributed Sensor Networks1550-14772017-07-011310.1177/1550147717717593Distributed and morphological operation-based data collection algorithmYalin Nie0Haijun Wang1Yujie Qin2Zeyu Sun3School of Computer and Information Engineering, Luoyang Institute of Science and Technology, Luoyang, ChinaSchool of Mathematics and Statistics, Henan University of Science and Technology, Luoyang, ChinaSchool of Computer and Information Engineering, Luoyang Institute of Science and Technology, Luoyang, ChinaSchool of Computer and Information Engineering, Luoyang Institute of Science and Technology, Luoyang, ChinaWhen monitoring the environment with wireless sensor networks, the data sensed by the nodes within event backbone regions can adequately represent the events. As a result, identifying event backbone regions is a key issue for wireless sensor networks. With this aim, we propose a distributed and morphological operation-based data collection algorithm. Inspired by the use of morphological erosion and dilation on binary images, the proposed distributed and morphological operation-based data collection algorithm calculates the structuring neighbors of each node based on the structuring element, and it produces an event-monitoring map of structuring neighbors with less cost and then determines whether to erode or not. The remaining nodes that are not eroded become the event backbone nodes and send their sensing data. Moreover, according to the event backbone regions, the sink can approximately recover the complete event regions by the dilation operation. The algorithm analysis and experimental results show that the proposed algorithm can lead to lower overhead, decrease the amount of transmitted data, prolong the network lifetime, and rapidly recover event regions.https://doi.org/10.1177/1550147717717593 |
| spellingShingle | Yalin Nie Haijun Wang Yujie Qin Zeyu Sun Distributed and morphological operation-based data collection algorithm International Journal of Distributed Sensor Networks |
| title | Distributed and morphological operation-based data collection algorithm |
| title_full | Distributed and morphological operation-based data collection algorithm |
| title_fullStr | Distributed and morphological operation-based data collection algorithm |
| title_full_unstemmed | Distributed and morphological operation-based data collection algorithm |
| title_short | Distributed and morphological operation-based data collection algorithm |
| title_sort | distributed and morphological operation based data collection algorithm |
| url | https://doi.org/10.1177/1550147717717593 |
| work_keys_str_mv | AT yalinnie distributedandmorphologicaloperationbaseddatacollectionalgorithm AT haijunwang distributedandmorphologicaloperationbaseddatacollectionalgorithm AT yujieqin distributedandmorphologicaloperationbaseddatacollectionalgorithm AT zeyusun distributedandmorphologicaloperationbaseddatacollectionalgorithm |