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صفحه اصلی
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سی و سومین کنفرانس بین المللی مهندسی برق
Devloping a clustering routing algorithm based on the efficient hybrid methodology for WSN performance optimization
نویسندگان :
Neda Mazloomi
1
Sajad Haghzad Klidbary
2
1- University of Zanjan
2- University of Zanjan
کلمات کلیدی :
Wireless Sensor Network (WSN)،Genetic Algorithm (GA)،Decision Tree،Ant Colony Optimization (ACO)،Butterfly Optimization Algorithm (BOA)
چکیده :
Wireless sensor networks (WSNs) play a crucial role in environmental, security, and health monitoring, but they face significant challenges, including energy consumption and routing complexity. This paper introduces a novel optimization approach for WSNs using four intelligent algorithms: decision tree, genetic algorithm (GA), butterfly optimization algorithm (BOA), and ant colony optimization (ACO). These algorithms contribute to reducing energy consumption and enhancing network performance, particularly in clustering and routing. Simulation results demonstrate that the proposed method outperforms other algorithms, such as LEACH, DEEC, and HEED, in terms of reducing energy consumption and increasing the number of packets transmitted to the base station. The overall improvement of the proposed method over the best performing algorithm, HEED, is approximately 16.7% in terms of increasing the total residual energy. Regarding the number of alive nodes, the proposed method also outperforms other approaches, showing an improvement of about 9.6% compared to HEED. Specifically, while HEED transmitted about 2.9 units of packets, the proposed method transmits approximately 3.8 packets to the base station, representing a 31% improvement. These results indicate that the proposed method not only manages energy more effectively but also significantly enhances the data transmission efficiency to the base station, thus improving the overall performance of the WSN in terms of both energy efficiency and network reliability.
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