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Energy-efficient resource allocation for Fifth Generation (5G) and the wireless networks has become a primary research challenge because of enhancing the small cells (SC) concentrations and maximum Quality of Experience (QoE) necessities for the professional handlers. Make sure the QoE as well as energy effectiveness in important in mobile networks, however, these aims are continuously conflicting and hardly solved simultaneously in previous solutions. Hence, this research proposes the Kent mapping-based butterfly optimization algorithm (KM-BOA) approach for the energy-efficient resource management-based clustering for the wireless networks. The KM-BOA approach efficiently allocates resources such as bandwidth, power as well as computation to minimize an energy consumption in wireless networks, particularly for devices with constrained battery life. The proposed KM-BOA approach attains the better energy efficiency of 13.6, 13.9, 14.5, 14.9, and 15.1 based on the number of iterations of 2, 4, 6, 8, and 10, respectively, as compared to the existing methods like modified K-means clustering approach.

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Energy-Efficient Resource Management and Clustering for the Wireless Networks Using Kent Mapping-Based Butterfly Optimization Algorithm

  • 章节

  • 发表日期：

    2026年

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  • Sowmya Madhavan,
  • G. S. Nijaguna,
  • B. A. Smitha,
  • R. Rana Veer Samara Sihman Bharattej,
  • R. Mohan Naik

摘要

Energy-efficient resource allocation for Fifth Generation (5G) and the wireless networks has become a primary research challenge because of enhancing the small cells (SC) concentrations and maximum Quality of Experience (QoE) necessities for the professional handlers. Make sure the QoE as well as energy effectiveness in important in mobile networks, however, these aims are continuously conflicting and hardly solved simultaneously in previous solutions. Hence, this research proposes the Kent mapping-based butterfly optimization algorithm (KM-BOA) approach for the energy-efficient resource management-based clustering for the wireless networks. The KM-BOA approach efficiently allocates resources such as bandwidth, power as well as computation to minimize an energy consumption in wireless networks, particularly for devices with constrained battery life. The proposed KM-BOA approach attains the better energy efficiency of 13.6, 13.9, 14.5, 14.9, and 15.1 based on the number of iterations of 2, 4, 6, 8, and 10, respectively, as compared to the existing methods like modified K-means clustering approach.