Area Coverage Maximization under Connectivity Constraint in Wireless Sensor Networks
Wireless sensor networks (WSNs) have several important applications, both in research and domestic use. Generally, their main role is to collect and transmit data from an ROI (region of interest) to a base station for processing and analysis. Therefore, it is vital to ensure maximum coverage of the...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/5/1712 |
| _version_ | 1797473886568185856 |
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| author | Frantz Tossa Wahabou Abdou Keivan Ansari Eugène C. Ezin Pierre Gouton |
| author_facet | Frantz Tossa Wahabou Abdou Keivan Ansari Eugène C. Ezin Pierre Gouton |
| author_sort | Frantz Tossa |
| collection | DOAJ |
| description | Wireless sensor networks (WSNs) have several important applications, both in research and domestic use. Generally, their main role is to collect and transmit data from an ROI (region of interest) to a base station for processing and analysis. Therefore, it is vital to ensure maximum coverage of the chosen area and communication between the nodes forming the network. A major problem in network design is the deployment of sensors with the aim to ensure both maximum coverage and connectivity between sensor node. The maximum coverage problem addressed here focuses on calculating the area covered by the deployed sensor nodes. Thus, we seek to cover any type of area (regular or irregular shape) with a predefined number of homogeneous sensors using a genetic algorithm to find the best placement to ensure maximum network coverage under the constraint of connectivity between the sensors. Therefore, this paper tackles the dual problem of maximum coverage and connectivity between sensor nodes. We define the maximum coverage and connectivity problems and then propose a mathematical model and a complex objective function. The results show that the algorithm, called GAFACM (Genetic Algorithm For Area Coverage Maximization), covers all forms of the area for a given number of sensors and finds the best positions to maximize coverage within the area of interest while guaranteeing the connectivity between the sensors. |
| first_indexed | 2024-03-09T20:22:51Z |
| format | Article |
| id | doaj.art-f53da01322024bae801f3534d7d5d6a2 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T20:22:51Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-f53da01322024bae801f3534d7d5d6a22023-11-23T23:44:57ZengMDPI AGSensors1424-82202022-02-01225171210.3390/s22051712Area Coverage Maximization under Connectivity Constraint in Wireless Sensor NetworksFrantz Tossa0Wahabou Abdou1Keivan Ansari2Eugène C. Ezin3Pierre Gouton4ImViA Laboratory, University of Bourgogne Franche-Comté, 21000 Dijon, FranceLIB Laboratory, University of Bourgogne Franche-Comté, 21000 Dijon, FranceInstitute for Color Science and Technology, Tehran 1668836471, IranLETIA Laboratory, University of Abomey-Calavi, Abomey-Calavi BP 2549, BeninImViA Laboratory, University of Bourgogne Franche-Comté, 21000 Dijon, FranceWireless sensor networks (WSNs) have several important applications, both in research and domestic use. Generally, their main role is to collect and transmit data from an ROI (region of interest) to a base station for processing and analysis. Therefore, it is vital to ensure maximum coverage of the chosen area and communication between the nodes forming the network. A major problem in network design is the deployment of sensors with the aim to ensure both maximum coverage and connectivity between sensor node. The maximum coverage problem addressed here focuses on calculating the area covered by the deployed sensor nodes. Thus, we seek to cover any type of area (regular or irregular shape) with a predefined number of homogeneous sensors using a genetic algorithm to find the best placement to ensure maximum network coverage under the constraint of connectivity between the sensors. Therefore, this paper tackles the dual problem of maximum coverage and connectivity between sensor nodes. We define the maximum coverage and connectivity problems and then propose a mathematical model and a complex objective function. The results show that the algorithm, called GAFACM (Genetic Algorithm For Area Coverage Maximization), covers all forms of the area for a given number of sensors and finds the best positions to maximize coverage within the area of interest while guaranteeing the connectivity between the sensors.https://www.mdpi.com/1424-8220/22/5/1712wireless sensor networkssensors deploymentarea coverageconnectivitygenetic algorithm |
| spellingShingle | Frantz Tossa Wahabou Abdou Keivan Ansari Eugène C. Ezin Pierre Gouton Area Coverage Maximization under Connectivity Constraint in Wireless Sensor Networks Sensors wireless sensor networks sensors deployment area coverage connectivity genetic algorithm |
| title | Area Coverage Maximization under Connectivity Constraint in Wireless Sensor Networks |
| title_full | Area Coverage Maximization under Connectivity Constraint in Wireless Sensor Networks |
| title_fullStr | Area Coverage Maximization under Connectivity Constraint in Wireless Sensor Networks |
| title_full_unstemmed | Area Coverage Maximization under Connectivity Constraint in Wireless Sensor Networks |
| title_short | Area Coverage Maximization under Connectivity Constraint in Wireless Sensor Networks |
| title_sort | area coverage maximization under connectivity constraint in wireless sensor networks |
| topic | wireless sensor networks sensors deployment area coverage connectivity genetic algorithm |
| url | https://www.mdpi.com/1424-8220/22/5/1712 |
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