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DC Field | Value | Language |
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dc.contributor.author | Odeh, Prince O. | - |
dc.contributor.author | Zubair, Suleiman | - |
dc.contributor.author | USMAN, Abraham Usman | - |
dc.date.accessioned | 2022-12-22T14:32:47Z | - |
dc.date.available | 2022-12-22T14:32:47Z | - |
dc.date.issued | 2021 | - |
dc.identifier.uri | http://repository.futminna.edu.ng:8080/jspui/handle/123456789/15827 | - |
dc.description.abstract | Energy saving is an essential consideration when designing efficient wireless sensor networks. The overall energy consumption of the sensor nodes (SNs) in a network determines the lifespan of that network. This paper addressed issue of nodes competing for channel resource that leads to energy wasted through idle listening and overhearing. Contention window adjustment was utilized with Low Energy Adaptive Clustering Hierarchy (LEACH) to combat this challenge for energy efficient utilization and distribution. This technique is termed Contention Window Adjustment LEACH (CW LEACH). This clustering technique extends a network’s lifetime by minimizing energy wasted on idle listening and creating efficient energy distribution within the network. The simulation for this technique was done on MATLAB. The total round of successful transmission before the network collapse was 2929; the number of transmissions was 2400 and the average energy consumed for the full life cycle for 1000 nodes observed under simulation was 0.25J at peak of operation. This technique has a future in implementation on 5G with large number of connected devices. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Conference Proceedings of 1st International Conference on Data Science and Engineering | en_US |
dc.subject | Cluster, Contention window, LEACH, M2M, Routing protocol | en_US |
dc.title | Leach with Contention Window Adjustment for Optimum Performance in Energy Distribution and Efficient Utilization | en_US |
dc.type | Article | en_US |
Appears in Collections: | Telecommunication Engineering |
Files in This Item:
File | Description | Size | Format | |
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AFIT conference.pdf | 1.21 MB | Adobe PDF | View/Open |
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