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<p>Wireless body area networks (WBANs) play a critical role in health monitoring but are constrained by rapid energy depletion, node overheating, and network congestion, which degrade quality of service and system reliability. To tackle these challenges, this paper proposes ETC-MOTLBO, an energy-, temperature-, and congestion-aware multi-objective teaching–learning-based optimization framework integrated with software-defined networking (SDN). The approach employs K-means clustering to organize sensor nodes efficiently and uses a centralized SDN controller with a multi-objective fitness function considering residual energy, node temperature, queue length, and intra-cluster distances to optimize cluster head selection and routing paths dynamically. Simulation results demonstrate that, compared to conventional methods, ETC-MOTLBO reduces average energy consumption to as low as 0.66 J, extends network lifetime up to 1990 rounds, maintains a high data delivery rate above 99.98%, and effectively limits end-to-end delay to under 3.82 s even at higher node densities. These improvements confirm that the proposed method significantly enhances energy efficiency, thermal stability, and congestion control, offering a robust and scalable solution for reliable WBAN-SDN communication in healthcare environments. </p>

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Energy and temperature-aware routing approach for congestion control in wireless body area networks

  • 期刊论文

  • 发表日期：

    2025年7月11日

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  • Javad Mozaffari,
  • Mohammad Abdollahi Azgomi,
  • Halimeh Madadi,
  • Mohammad Reza Ebrahimi Dishabi

摘要

Wireless body area networks (WBANs) play a critical role in health monitoring but are constrained by rapid energy depletion, node overheating, and network congestion, which degrade quality of service and system reliability. To tackle these challenges, this paper proposes ETC-MOTLBO, an energy-, temperature-, and congestion-aware multi-objective teaching–learning-based optimization framework integrated with software-defined networking (SDN). The approach employs K-means clustering to organize sensor nodes efficiently and uses a centralized SDN controller with a multi-objective fitness function considering residual energy, node temperature, queue length, and intra-cluster distances to optimize cluster head selection and routing paths dynamically. Simulation results demonstrate that, compared to conventional methods, ETC-MOTLBO reduces average energy consumption to as low as 0.66 J, extends network lifetime up to 1990 rounds, maintains a high data delivery rate above 99.98%, and effectively limits end-to-end delay to under 3.82 s even at higher node densities. These improvements confirm that the proposed method significantly enhances energy efficiency, thermal stability, and congestion control, offering a robust and scalable solution for reliable WBAN-SDN communication in healthcare environments.