A Distributed Energy-Throughput Efficient Cross-Layer Framework Using Hybrid Optimization Algorithm
Magnetic induction (MI)-operated wireless sensor networks (WSNs), due to their similar performance in air, underwater, and underground mediums, are rapidly emerging networks that offer a wide range of applications, including mine prevention, power grid maintenance, underground pipeline monitoring, a...
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MDPI AG
2025-01-01
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| Series: | Mathematics |
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| author | Pratap Singh Nitin Mittal Vikas Mittal Tapankumar Trivedi Ashish Singh Szymon Łukasik Rohit Salgotra |
| author_facet | Pratap Singh Nitin Mittal Vikas Mittal Tapankumar Trivedi Ashish Singh Szymon Łukasik Rohit Salgotra |
| author_sort | Pratap Singh |
| collection | DOAJ |
| description | Magnetic induction (MI)-operated wireless sensor networks (WSNs), due to their similar performance in air, underwater, and underground mediums, are rapidly emerging networks that offer a wide range of applications, including mine prevention, power grid maintenance, underground pipeline monitoring, and upstream oil monitoring. MI-based wireless underground sensor networks (WUSNs), utilizing small antenna coils, offer a viable solution by providing consistent channel conditions. The cross-layer protocols address the specific challenges of WUSNs, leading to improved network performance and enhanced operational capabilities in real-world applications. This work proposes a distributed cross-layer solution, leveraging the hybrid marine predator naked mole rat algorithm (MPNMRA) for MI-operated WUSNs. The solution, called DECMN (distributed energy-throughput efficient cross-layer network using MPNMRA), is designed to optimize the MI communication channels, MI relay coils (MI waveguide), and MI waveguide with 3D coils to fulfill quality of service (QoS) parameters, while achieving energy savings and throughput gains. DECMN utilizes the interactions between various layers to develop cross-layer protocols based on MPNMRA. Simulation results demonstrate the effectiveness of DECMN, offering energy savings, increased throughput, and reliable transmissions within the performance limits. |
| format | Article |
| id | doaj-art-c3aeccc8b86f4dfcbb04343af8fcea14 |
| institution | Kabale University |
| issn | 2227-7390 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj-art-c3aeccc8b86f4dfcbb04343af8fcea142025-01-24T13:39:48ZengMDPI AGMathematics2227-73902025-01-0113222410.3390/math13020224A Distributed Energy-Throughput Efficient Cross-Layer Framework Using Hybrid Optimization AlgorithmPratap Singh0Nitin Mittal1Vikas Mittal2Tapankumar Trivedi3Ashish Singh4Szymon Łukasik5Rohit Salgotra6Department of Computer Science and Engineering, Guru Jambheshwar University of Science & Technology, Hisar 125001, IndiaDepartment of Industry 4.0, Shri Vishwakarma Skill University, Palwal 121102, IndiaDepartment of Electronics and Communication Engineering, Chandigarh University, Mohali 140413, IndiaMarwadi University Research Center, Department of Electrical Engineering, Faculty of Engineering & Technology, Marwadi University, Rajkot 360003, IndiaNIMS School of Electrical and Electronics Engineering, NIMS University Rajasthan, Jaipur 303121, IndiaFaculty of Physics and Applied Computer Science, AGH University of Krakow, 30-059 Krakow, PolandFaculty of Physics and Applied Computer Science, AGH University of Krakow, 30-059 Krakow, PolandMagnetic induction (MI)-operated wireless sensor networks (WSNs), due to their similar performance in air, underwater, and underground mediums, are rapidly emerging networks that offer a wide range of applications, including mine prevention, power grid maintenance, underground pipeline monitoring, and upstream oil monitoring. MI-based wireless underground sensor networks (WUSNs), utilizing small antenna coils, offer a viable solution by providing consistent channel conditions. The cross-layer protocols address the specific challenges of WUSNs, leading to improved network performance and enhanced operational capabilities in real-world applications. This work proposes a distributed cross-layer solution, leveraging the hybrid marine predator naked mole rat algorithm (MPNMRA) for MI-operated WUSNs. The solution, called DECMN (distributed energy-throughput efficient cross-layer network using MPNMRA), is designed to optimize the MI communication channels, MI relay coils (MI waveguide), and MI waveguide with 3D coils to fulfill quality of service (QoS) parameters, while achieving energy savings and throughput gains. DECMN utilizes the interactions between various layers to develop cross-layer protocols based on MPNMRA. Simulation results demonstrate the effectiveness of DECMN, offering energy savings, increased throughput, and reliable transmissions within the performance limits.https://www.mdpi.com/2227-7390/13/2/224distributed power controldistributed protocolwireless underground sensor networkNMRAMPAMPNMRA |
| spellingShingle | Pratap Singh Nitin Mittal Vikas Mittal Tapankumar Trivedi Ashish Singh Szymon Łukasik Rohit Salgotra A Distributed Energy-Throughput Efficient Cross-Layer Framework Using Hybrid Optimization Algorithm Mathematics distributed power control distributed protocol wireless underground sensor network NMRA MPA MPNMRA |
| title | A Distributed Energy-Throughput Efficient Cross-Layer Framework Using Hybrid Optimization Algorithm |
| title_full | A Distributed Energy-Throughput Efficient Cross-Layer Framework Using Hybrid Optimization Algorithm |
| title_fullStr | A Distributed Energy-Throughput Efficient Cross-Layer Framework Using Hybrid Optimization Algorithm |
| title_full_unstemmed | A Distributed Energy-Throughput Efficient Cross-Layer Framework Using Hybrid Optimization Algorithm |
| title_short | A Distributed Energy-Throughput Efficient Cross-Layer Framework Using Hybrid Optimization Algorithm |
| title_sort | distributed energy throughput efficient cross layer framework using hybrid optimization algorithm |
| topic | distributed power control distributed protocol wireless underground sensor network NMRA MPA MPNMRA |
| url | https://www.mdpi.com/2227-7390/13/2/224 |
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