An energy-aware protocol in wireless sensor networks using the scattered search algorithm and fuzzy logic

Given the resource limitations of wireless sensor networks (WSNs), energy conservation is of utmost importance. Moreover, minimizing data collection delays is crucial to maintaining data freshness. Additionally, it is desirable to increase the number of collected data samples to enhance accuracy and robustness in data collection. For this purpose, this research article proposes a clustering-based routing protocol aimed at maximizing the delivery of data samples while minimizing energy consumption and data collection delays. The protocol employs a scattered search algorithm and fuzzy logic to cluster the sensor nodes. By considering the distance to the sink and the remaining energy level of the battery, the network is dynamically divided into clusters using a lightweight clustering approach. To evaluate the effectiveness of the proposed method, simulations were conducted in OPNET using the AFSRP protocol. The results demonstrate superior performance of the proposed method in terms of end-to-end delay by 13.44%, media access delay by 75.2%, throughput rate by 20.55%, energy consumption by 13.52%, signal-to-noise ratio by 43.40% and delivery rate of successfully sending data to the sink is 0.21% higher than the well-known AFSRP method.

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Publication Details

Journal
PLoS ONE
Published
2024-11-04
DOI
https://doi.org/10.1371/journal.pone.0297728
Citations
3
Primary Topic
Energy Efficient Wireless Sensor Networks
Type
article
Field-Weighted Citation Impact
1.05
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article

An energy-aware protocol in wireless sensor networks using the scattered search algorithm and fuzzy logic

Shayesteh Tabatabaei
3 citations
PLoS ONE
Energy Efficient Wireless Sensor Networks
1.05
article

An energy-aware protocol in wireless sensor networks using the scattered search algorithm and fuzzy logic

Shayesteh Tabatabaei
article en
3 citations

Abstract

Given the resource limitations of wireless sensor networks (WSNs), energy conservation is of utmost importance. Moreover, minimizing data collection delays is crucial to maintaining data freshness. Additionally, it is desirable to increase the number of collected data samples to enhance accuracy and robustness in data collection. For this purpose, this research article proposes a clustering-based routing protocol aimed at maximizing the delivery of data samples while minimizing energy consumption and data collection delays. The protocol employs a scattered search algorithm and fuzzy logic to cluster the sensor nodes. By considering the distance to the sink and the remaining energy level of the battery, the network is dynamically divided into clusters using a lightweight clustering approach. To evaluate the effectiveness of the proposed method, simulations were conducted in OPNET using the AFSRP protocol. The results demonstrate superior performance of the proposed method in terms of end-to-end delay by 13.44%, media access delay by 75.2%, throughput rate by 20.55%, energy consumption by 13.52%, signal-to-noise ratio by 43.40% and delivery rate of successfully sending data to the sink is 0.21% higher than the well-known AFSRP method.

PLoS ONEVol. 19(11)
Affordable and clean energy
Openalex Percentile: Top 21%
Energy Efficient Wireless Sensor Networks
1.05
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