3-D Terrain Node Coverage of Wireless Sensor Network Using Enhanced Black Hole Algorithm
In this paper, a new intelligent computing algorithm named Enhanced Black Hole (EBH) is proposed to which the mutation operation and weight factor are applied. In EBH, several elites are taken as role models instead of only one in the original Black Hole (BH) algorithm. The performance of the EBH al...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-04-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/20/8/2411 |
| _version_ | 1797569759314706432 |
|---|---|
| author | Jeng-Shyang Pan Qing-Wei Chai Shu-Chuan Chu Ning Wu |
| author_facet | Jeng-Shyang Pan Qing-Wei Chai Shu-Chuan Chu Ning Wu |
| author_sort | Jeng-Shyang Pan |
| collection | DOAJ |
| description | In this paper, a new intelligent computing algorithm named Enhanced Black Hole (EBH) is proposed to which the mutation operation and weight factor are applied. In EBH, several elites are taken as role models instead of only one in the original Black Hole (BH) algorithm. The performance of the EBH algorithm is verified by the CEC 2013 test suit, and shows better results than the original BH. In addition, the EBH and other celebrated algorithms can be used to solve node coverage problems of Wireless Sensor Network (WSN) in 3-D terrain with satisfactory performance. |
| first_indexed | 2024-03-10T20:16:06Z |
| format | Article |
| id | doaj.art-1a8aca3b2b024047958f6fbe5856dc86 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T20:16:06Z |
| publishDate | 2020-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-1a8aca3b2b024047958f6fbe5856dc862023-11-19T22:31:12ZengMDPI AGSensors1424-82202020-04-01208241110.3390/s200824113-D Terrain Node Coverage of Wireless Sensor Network Using Enhanced Black Hole AlgorithmJeng-Shyang Pan0Qing-Wei Chai1Shu-Chuan Chu2Ning Wu3College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, ChinaCollege of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, ChinaSchool of Electronic and Information Engineering, Beibu Gulf University, Qinzhou 535011, ChinaIn this paper, a new intelligent computing algorithm named Enhanced Black Hole (EBH) is proposed to which the mutation operation and weight factor are applied. In EBH, several elites are taken as role models instead of only one in the original Black Hole (BH) algorithm. The performance of the EBH algorithm is verified by the CEC 2013 test suit, and shows better results than the original BH. In addition, the EBH and other celebrated algorithms can be used to solve node coverage problems of Wireless Sensor Network (WSN) in 3-D terrain with satisfactory performance.https://www.mdpi.com/1424-8220/20/8/2411node coverage3-D node deployedWSNintelligence computingblack hole |
| spellingShingle | Jeng-Shyang Pan Qing-Wei Chai Shu-Chuan Chu Ning Wu 3-D Terrain Node Coverage of Wireless Sensor Network Using Enhanced Black Hole Algorithm Sensors node coverage 3-D node deployed WSN intelligence computing black hole |
| title | 3-D Terrain Node Coverage of Wireless Sensor Network Using Enhanced Black Hole Algorithm |
| title_full | 3-D Terrain Node Coverage of Wireless Sensor Network Using Enhanced Black Hole Algorithm |
| title_fullStr | 3-D Terrain Node Coverage of Wireless Sensor Network Using Enhanced Black Hole Algorithm |
| title_full_unstemmed | 3-D Terrain Node Coverage of Wireless Sensor Network Using Enhanced Black Hole Algorithm |
| title_short | 3-D Terrain Node Coverage of Wireless Sensor Network Using Enhanced Black Hole Algorithm |
| title_sort | 3 d terrain node coverage of wireless sensor network using enhanced black hole algorithm |
| topic | node coverage 3-D node deployed WSN intelligence computing black hole |
| url | https://www.mdpi.com/1424-8220/20/8/2411 |
| work_keys_str_mv | AT jengshyangpan 3dterrainnodecoverageofwirelesssensornetworkusingenhancedblackholealgorithm AT qingweichai 3dterrainnodecoverageofwirelesssensornetworkusingenhancedblackholealgorithm AT shuchuanchu 3dterrainnodecoverageofwirelesssensornetworkusingenhancedblackholealgorithm AT ningwu 3dterrainnodecoverageofwirelesssensornetworkusingenhancedblackholealgorithm |