Relocating Sensor Nodes to Maximize Cumulative Connected Coverage in Wireless Sensor Networks
In order to extend the availability of the wireless sensor network and to extract maximum possible information from the surveillance area, proper usage of the power capacity of the sensor nodes is important. Our work describes a dynamic relocation algorithm called MaxNetLife, which is mainly based o...
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| Format: | Article |
| Language: | English |
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MDPI AG
2008-04-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/8/4/2792/ |
| _version_ | 1811298581510881280 |
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| author | Vedat Coskun |
| author_facet | Vedat Coskun |
| author_sort | Vedat Coskun |
| collection | DOAJ |
| description | In order to extend the availability of the wireless sensor network and to extract maximum possible information from the surveillance area, proper usage of the power capacity of the sensor nodes is important. Our work describes a dynamic relocation algorithm called MaxNetLife, which is mainly based on utilizing the remaining power of individual sensor nodes as well as properly relocating sensor nodes so that all sensor nodes can transmit the data they sense to the sink. Hence, the algorithm maximizes total collected information from the surveillance area before the possible death of the sensor network by increasing cumulative connected coverage parameter of the network. A deterministic approach is used to deploy sensor nodes into the sensor field where Hexagonal Grid positioning is used to address and locate each sensor node. Sensor nodes those are not planned to be actively used in the close future in a specific cell are preemptively relocated to the cells those will be in need of additional sensor nodes to improve cumulative connected coverage of the network. MaxNetLife algorithm also includes the details of the relocation activities, which include preemptive migration of the redundant nodes to the cells before any coverage hole occurs because of death of a sensor node. Relocation Model, Data Aggregation Model, and Energy model of the algorithm are studied in detail. MaxNetLife algorithm is proved to be effective, scalable, and applicable through simulations. |
| first_indexed | 2024-04-13T06:21:25Z |
| format | Article |
| id | doaj.art-fef39f54436b4d97a0e07648baf9f0ed |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T06:21:25Z |
| publishDate | 2008-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-fef39f54436b4d97a0e07648baf9f0ed2022-12-22T02:58:38ZengMDPI AGSensors1424-82202008-04-018427922817Relocating Sensor Nodes to Maximize Cumulative Connected Coverage in Wireless Sensor NetworksVedat CoskunIn order to extend the availability of the wireless sensor network and to extract maximum possible information from the surveillance area, proper usage of the power capacity of the sensor nodes is important. Our work describes a dynamic relocation algorithm called MaxNetLife, which is mainly based on utilizing the remaining power of individual sensor nodes as well as properly relocating sensor nodes so that all sensor nodes can transmit the data they sense to the sink. Hence, the algorithm maximizes total collected information from the surveillance area before the possible death of the sensor network by increasing cumulative connected coverage parameter of the network. A deterministic approach is used to deploy sensor nodes into the sensor field where Hexagonal Grid positioning is used to address and locate each sensor node. Sensor nodes those are not planned to be actively used in the close future in a specific cell are preemptively relocated to the cells those will be in need of additional sensor nodes to improve cumulative connected coverage of the network. MaxNetLife algorithm also includes the details of the relocation activities, which include preemptive migration of the redundant nodes to the cells before any coverage hole occurs because of death of a sensor node. Relocation Model, Data Aggregation Model, and Energy model of the algorithm are studied in detail. MaxNetLife algorithm is proved to be effective, scalable, and applicable through simulations.http://www.mdpi.com/1424-8220/8/4/2792/wireless sensor networkmobilityclusteringnetwork lifetime |
| spellingShingle | Vedat Coskun Relocating Sensor Nodes to Maximize Cumulative Connected Coverage in Wireless Sensor Networks Sensors wireless sensor network mobility clustering network lifetime |
| title | Relocating Sensor Nodes to Maximize Cumulative Connected Coverage in Wireless Sensor Networks |
| title_full | Relocating Sensor Nodes to Maximize Cumulative Connected Coverage in Wireless Sensor Networks |
| title_fullStr | Relocating Sensor Nodes to Maximize Cumulative Connected Coverage in Wireless Sensor Networks |
| title_full_unstemmed | Relocating Sensor Nodes to Maximize Cumulative Connected Coverage in Wireless Sensor Networks |
| title_short | Relocating Sensor Nodes to Maximize Cumulative Connected Coverage in Wireless Sensor Networks |
| title_sort | relocating sensor nodes to maximize cumulative connected coverage in wireless sensor networks |
| topic | wireless sensor network mobility clustering network lifetime |
| url | http://www.mdpi.com/1424-8220/8/4/2792/ |
| work_keys_str_mv | AT vedatcoskun relocatingsensornodestomaximizecumulativeconnectedcoverageinwirelesssensornetworks |