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. 2022 Mar 14;12(1):4381.
doi: 10.1038/s41598-022-08075-6.

A hybrid approach to enhance the lifespan of WSNs in nuclear power plant monitoring system

Md Ershadul Haque  1   2 , Tanvir Hossain  2 , Mahidur R Sarker  3 , Manoranjan Paul  1 , Md Samiul Hoque  2 , Salah Uddin  2 , Abdulla Al Suman  4 , Mohamad Hanif Md Saad  5 , Tanvir Ul Huque  6
Affiliations

A hybrid approach to enhance the lifespan of WSNs in nuclear power plant monitoring system

Md Ershadul Haque et al. Sci Rep. .

Abstract

In recent years, the nuclear power plant has received huge attention as it generates vast amounts of power at a lower cost. However, its creation of radioactive wastes is a major environmental concern. Therefore, the nuclear power plant requires a reliable and uninterrupted monitoring system as an essential part of it. Monitoring a nuclear power plant using wireless sensor networks is a convenient and popular practice now. This paper proposes a hybrid approach for monitoring wireless sensor networks in the context of a nuclear power plant in Bangladesh. Our hybrid approach enhances the lifespan of wireless sensor networks reducing power consumption and offering better connectivity of sensors. To do so, it uses both the topology maintenance and topology construction algorithms. We found that the HGETRecRot topology maintenance algorithm enhances the network lifetime compared to other algorithms. This algorithm increases the communication and sensing coverage area but decreases the network performance. We also propose a prediction model, based on linear regression algorithm, that predicts the best combination of topology maintenance and topology construction algorithms.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
An imagination of WSNs employed nuclear power plant.
Figure 2
Figure 2
Two ray ground propagation model.
Figure 3
Figure 3
A system in the prospect of first order energy dissipation model.
Figure 4
Figure 4
The probabilistic sensing model.
Figure 5
Figure 5
A flowchart of the proposed approach.
Figure 6
Figure 6
A3Cov algorithm.
Figure 7
Figure 7
Actual evaluated alive node.
Figure 8
Figure 8
Actual evaluated active nodes reachable from sink.
Figure 9
Figure 9
Actual evaluated covered communication area.
Figure 10
Figure 10
Actual evaluated covered sensing area.
Figure 11
Figure 11
Alive node based on prediction model.
Figure 12
Figure 12
Active nodes reachable from sink based on prediction model.
Figure 13
Figure 13
Covered communication area based on prediction model.
Figure 14
Figure 14
Covered sensing area based on prediction model.
See this image and copyright information in PMC

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