Scholarlink

<p>Wireless sensor networks (WSN) have emerged as an innovative technology that has gained significant attention due to their applicability in various fields of healthcare, disaster management, and environmental monitoring. However, existing cluster-based routing approaches consistently suffer with challenges, such as inefficient Cluster Head (CH) rotation and suboptimal energy utilization, leading to reduced life expectancy, typically characterized by the death of the last active node. Therefore, an energy-aware multi-objective triple strategy-based zebra optimization algorithm (EMTSZOA) is proposed in this research to enhance the energy efficiency in WSNs. This model employs a triple strategy by combining a Sine Cosine Strategy (SCS), Dynamic Switching Probability (DSP), and Dynamic Adaptive Weight (DAW) factor. EMTSZOA is employed for the selection of an optimal Cluster Head (CH) using the fitness functions of the distance between the Sensor Nodes (SNs), distance between the CH and Base Station (BS), Location Factor (LF), Load Balancing Factor (LBF), and Mean Node Energy (MNE). Furthermore, the model’s efficient route determination mechanism from the CH to BS is designed for effective communication and energy optimization. The EMTSZOA is utilized to improve the life expectancy while enhancing the across the proposed setup. The proposed EMTSZOA is evaluated based on the number of alive and dead nodes, overall energy consumption, throughput, Packet Delivery Ratio (PDR), Packet Loss Ratio (PLR), and life expectancy. The life expectancy of EMTSZOA analyzed with 500 nodes is 93.80%, demonstrating superior capabilities than the energy-efficient lifetime aware cluster-based routing (EELCR) model, which achieves 83.14% life expectancy for the same amount of nodes.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Energy-aware multi-objective triple strategy-based zebra optimization algorithm for clustering and routing in wireless sensor network

  • 期刊论文

  • 发表日期：

    2025年7月29日

查看全文
  • Sunil M. Devprabhakar,
  • Manjunatha Parameswarappa,
  • Anil Kumar Jemla Naik

摘要

Wireless sensor networks (WSN) have emerged as an innovative technology that has gained significant attention due to their applicability in various fields of healthcare, disaster management, and environmental monitoring. However, existing cluster-based routing approaches consistently suffer with challenges, such as inefficient Cluster Head (CH) rotation and suboptimal energy utilization, leading to reduced life expectancy, typically characterized by the death of the last active node. Therefore, an energy-aware multi-objective triple strategy-based zebra optimization algorithm (EMTSZOA) is proposed in this research to enhance the energy efficiency in WSNs. This model employs a triple strategy by combining a Sine Cosine Strategy (SCS), Dynamic Switching Probability (DSP), and Dynamic Adaptive Weight (DAW) factor. EMTSZOA is employed for the selection of an optimal Cluster Head (CH) using the fitness functions of the distance between the Sensor Nodes (SNs), distance between the CH and Base Station (BS), Location Factor (LF), Load Balancing Factor (LBF), and Mean Node Energy (MNE). Furthermore, the model’s efficient route determination mechanism from the CH to BS is designed for effective communication and energy optimization. The EMTSZOA is utilized to improve the life expectancy while enhancing the across the proposed setup. The proposed EMTSZOA is evaluated based on the number of alive and dead nodes, overall energy consumption, throughput, Packet Delivery Ratio (PDR), Packet Loss Ratio (PLR), and life expectancy. The life expectancy of EMTSZOA analyzed with 500 nodes is 93.80%, demonstrating superior capabilities than the energy-efficient lifetime aware cluster-based routing (EELCR) model, which achieves 83.14% life expectancy for the same amount of nodes.