PSO-Controlled WSN Environment to Mitigate Flooding and Improve Network Lifetime
Nawkhare, Rahul; Singh, Daljeet
Nawkhare, Rahul
Singh, Daljeet
Engineering and Scientific Research Groups
Nawkhare, R. & Singh, D. (2024). PSO-Controlled WSN Environment to Mitigate Flooding and Improve Network Lifetime. Journal of electrical systems 20(3s), 1424-1436. https://journal.esrgroups.org/jes/article/view/1519/1246
https://creativecommons.org/licenses/by/4.0/
© JES 2024. Articles published in JES are distributed under the terms of the CC BY Licence.
https://creativecommons.org/licenses/by/4.0/
© JES 2024. Articles published in JES are distributed under the terms of the CC BY Licence.
https://creativecommons.org/licenses/by/4.0/
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202408145426
https://urn.fi/URN:NBN:fi:oulu-202408145426
Tiivistelmä
Abstract
The Restricted Flooding-based Route Discovery (RFBRD) –Particle Swarm Optimization (PSO) routing scheme introduced for Wireless Sensor Networks (WSNs) in this article not only reduces the energy loss due to unwanted RREQ (Route Request) flooding but also improves the lifetime of the network. Excessive flooding depletes energy and affects the lifetime of the network. Nodes in scarce regions are allowed to forward first and subsequent RREQ packets freely in the network and are relocated using PSO to improvetheir neighborhood for better neighbor connectivity and coverage. Whereas, nodes in the populated region or dense regionare governed by energy ratios and are allowed to forward first RREQ packets only when they satisfy the energy conditions. This scheme is efficient in maintaining a proper balance of QoS (Quality of Service) parameters works well for high-density networks for more than 50 nodes and can restructure network topology obtaining better connectivity. Experimental analysis showed that the performance of AODV is superior in the case of a low-density network (N=40 nodes) while RFBRD-PSO outperforms in all other configurations (60, 80, and 100 nodes). The Packet delivery ratio was increased by 0.08% and the throughput was higher by 11 kbps in the case of RFBRD-PSO. The routing overhead is low by approximately 40% and the average end-to-end delay is found low by 0.04 as compared to the AODV routing. The energy residue in the case of RFBRD-PSO is less than the value of AODV is the cost paid for a higher packet delivery ratio. The neighborhood connectivity is improved by approximately 32%
The Restricted Flooding-based Route Discovery (RFBRD) –Particle Swarm Optimization (PSO) routing scheme introduced for Wireless Sensor Networks (WSNs) in this article not only reduces the energy loss due to unwanted RREQ (Route Request) flooding but also improves the lifetime of the network. Excessive flooding depletes energy and affects the lifetime of the network. Nodes in scarce regions are allowed to forward first and subsequent RREQ packets freely in the network and are relocated using PSO to improvetheir neighborhood for better neighbor connectivity and coverage. Whereas, nodes in the populated region or dense regionare governed by energy ratios and are allowed to forward first RREQ packets only when they satisfy the energy conditions. This scheme is efficient in maintaining a proper balance of QoS (Quality of Service) parameters works well for high-density networks for more than 50 nodes and can restructure network topology obtaining better connectivity. Experimental analysis showed that the performance of AODV is superior in the case of a low-density network (N=40 nodes) while RFBRD-PSO outperforms in all other configurations (60, 80, and 100 nodes). The Packet delivery ratio was increased by 0.08% and the throughput was higher by 11 kbps in the case of RFBRD-PSO. The routing overhead is low by approximately 40% and the average end-to-end delay is found low by 0.04 as compared to the AODV routing. The energy residue in the case of RFBRD-PSO is less than the value of AODV is the cost paid for a higher packet delivery ratio. The neighborhood connectivity is improved by approximately 32%
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