Energy Efficient Routing in Cluster Based Heterogeneous Wireless Sensor Network Using Hybrid GWO and Firefly Algorithm

Dev, Jayashree; Mishra, Jibitesh

doi:10.1007/s11277-024-11447-y

Wireless Pers Commun

2024

DOI: 10.1007/s11277-024-11447-y

|View full text |Cite

Energy Efficient Routing in Cluster Based Heterogeneous Wireless Sensor Network Using Hybrid GWO and Firefly Algorithm

Jayashree Dev,

Jibitesh Mishra

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article2

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Transmission Performance Optimization of Wireless Sensor Networks Driven by Artificial Intelligence

Chunhui,

Pengwei,

Ping

et al. 2024

Applied Mathematics and Nonlinear Sciences

View full text Add to dashboard Cite

In this article, the transmission performance optimization of wireless sensor networks (WSN) is deeply studied, aiming at improving the transmission efficiency of WSN, reducing energy consumption and prolonging the network life through artificial intelligence (AI) technology. To accomplish the aforementioned goals, we devise an artificial intelligence-driven optimization model. This encompasses a detailed elucidation of the model’s conceptual framework, encompassing data preprocessing, feature selection, AI algorithm formulation, as well as verification and evaluation methodologies. Our experimental approach involves selecting representative WSN (Wireless Sensor Network) application contexts, with model efficacy validated through both simulated experiments and empirical investigations. The outcomes indicate that, when compared to the BPNN (Backpropagation Neural Network) technique, our proposed model notably enhances data transmission rates, mitigates latency and packet loss, and accomplishes superior energy management. It is concluded that artificial intelligence technology has obvious advantages in optimizing the transmission performance of WSN. A more efficient and reliable WSN system can be realized by intelligently sensing changes in network environment and dynamically adjusting transmission strategies.

show abstract

Transmission Performance Optimization of Wireless Sensor Networks Driven by Artificial Intelligence

Chunhui,

Pengwei,

Ping

et al. 2024

Applied Mathematics and Nonlinear Sciences

View full text Add to dashboard Cite

show abstract

Design and Performance Optimization of High Efficiency Wireless Sensor Network Data Transmission Algorithm

Chunhui,

Pengwei,

Ping

et al. 2024

Applied Mathematics and Nonlinear Sciences

View full text Add to dashboard Cite

Wireless Sensor Networks (WSN), as the cornerstone of modern Internet of Things (IoT) technology, achieve comprehensive perception and real-time transmission of physical world information by densely deploying small and lowpower sensor nodes in target areas, greatly promoting interconnectivity between people and things, and between things. However, the limited energy and communication capabilities of sensor nodes make efficient and reliable data transmission a major challenge in WSN design in a big data environment. To address this challenge, this paper proposes an innovative WSN data transmission optimization algorithm based on Ant Colony Optimization Neural Network (ACO-NN). This algorithm combines the global search capability of ACO with the powerful learning ability of neural networks. Specifically, the algorithm utilizes ACO to explore and accumulate pheromones on different paths, while using neural networks to evaluate and predict path quality, thereby guiding the selection and optimization of data transmission paths. The experimental results show that the algorithm proposed in this paper can significantly improve the efficiency and reliability of data transmission, reduce energy consumption, and extend network lifespan.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Energy Efficient Routing in Cluster Based Heterogeneous Wireless Sensor Network Using Hybrid GWO and Firefly Algorithm

Cited by 2 publications

References 25 publications

Transmission Performance Optimization of Wireless Sensor Networks Driven by Artificial Intelligence

Transmission Performance Optimization of Wireless Sensor Networks Driven by Artificial Intelligence

Design and Performance Optimization of High Efficiency Wireless Sensor Network Data Transmission Algorithm

Contact Info

Product

Resources

About