A novel genetic algorithm with db4 lifting for optimal sensor node placements
Joint Authors
Thangavel, Ganesan
Rajarajeswari, Pothuraju
Source
The International Arab Journal of Information Technology
Issue
Vol. 19, Issue 5 (30 Sep. 2022), pp.802-811, 10 p.
Publisher
Zarqa University Deanship of Scientific Research
Publication Date
2022-09-30
Country of Publication
Jordan
No. of Pages
10
Main Subjects
Information Technology and Computer Science
Abstract EN
Target coverage algorithms have considerable attention for monitoring the target point by dividing sensor nodes into cover groups, with each sensor cover group containing the target points.
When the number of sensors is restricted, optimal sensor node placement becomes a key task.
By placing sensors in the ideal position, the quality of maximum target coverage and node connectivity can be increased.
In this paper, a novel genetic algorithm based on the 2-D discrete Daubechies 4 (db4) lifting wavelet transform is proposed for determining the optimal sensor position.
Initially, the genetic algorithm identifies the population-based sensor location and 2-D discrete db4 lifting adjusts the sensor location into an optimal position where each sensor can cover a maximum number of targets that are connected to another sensor.
To demonstrate that the suggested model outperforms the existing method, A series of experiments are carried out using various situations to achieve maximum target point coverage, node interconnectivity, and network lifetime with a limited number of sensor nodes.
American Psychological Association (APA)
Thangavel, Ganesan& Rajarajeswari, Pothuraju. 2022. A novel genetic algorithm with db4 lifting for optimal sensor node placements. The International Arab Journal of Information Technology،Vol. 19, no. 5, pp.802-811.
https://search.emarefa.net/detail/BIM-1437090
Modern Language Association (MLA)
Thangavel, Ganesan& Rajarajeswari, Pothuraju. A novel genetic algorithm with db4 lifting for optimal sensor node placements. The International Arab Journal of Information Technology Vol. 19, no. 5 (Sep. 2022), pp.802-811.
https://search.emarefa.net/detail/BIM-1437090
American Medical Association (AMA)
Thangavel, Ganesan& Rajarajeswari, Pothuraju. A novel genetic algorithm with db4 lifting for optimal sensor node placements. The International Arab Journal of Information Technology. 2022. Vol. 19, no. 5, pp.802-811.
https://search.emarefa.net/detail/BIM-1437090
Data Type
Journal Articles
Language
English
Record ID
BIM-1437090