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<p>The evolution toward Sixth-Generation (6G) wireless networks is expected to transform the Internet of Health Things (IoHT) by enabling ultra-reliable low-latency communication (URLLC), energy-aware networking, and intelligent resource management for mission-critical healthcare applications. However, achieving these goals in large-scale IoHT deployments remains challenging, due to unbalanced energy consumption from static clustering, increased latency under dynamic traffic loads, reduced packet reliability in high-interference environments, and inefficiencies in maintaining information freshness. To address these challenges, this paper presents a novel 6G-Enabled Next-Generation Energy-Aware Node Clustering (6G-NENC) framework, specifically designed to leverage 6G-native features such as adaptive spectrum utilization, AI-driven resource allocation, and real-time channel-state monitoring. The proposed approach incorporates a dynamic cluster-head selection mechanism based on instantaneous link quality and residual energy, coupled with link-adaptive and load-balanced data-forwarding strategies. These design choices ensure reduced end-to-end delay, improved reliability, and prolonged network lifetime, even in mobility-intensive IoHT environments. The framework’s performance is validated through extensive simulations under diverse network densities, traffic models, and channel conditions, and compared with several state-of-the-art protocols. Key performance indicators such as latency, packet delivery ratio (PDR), energy consumption, throughput, and Age-of-Information (AoI), consistently demonstrate that 6G-NENC delivers superior efficiency, robustness, and scalability. The results highlight its potential as a foundational architecture for next-generation IoHT systems requiring stringent quality-of-service and quality-of-experience guarantees.</p>

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6G-enabled next-generation energy-aware node clustering technique for ultra-reliable low-latency in internet of health things

  • 期刊论文

  • 发表日期：

    2026年6月1日

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  • Altaf Hussain,
  • Tariq Hussain

摘要

The evolution toward Sixth-Generation (6G) wireless networks is expected to transform the Internet of Health Things (IoHT) by enabling ultra-reliable low-latency communication (URLLC), energy-aware networking, and intelligent resource management for mission-critical healthcare applications. However, achieving these goals in large-scale IoHT deployments remains challenging, due to unbalanced energy consumption from static clustering, increased latency under dynamic traffic loads, reduced packet reliability in high-interference environments, and inefficiencies in maintaining information freshness. To address these challenges, this paper presents a novel 6G-Enabled Next-Generation Energy-Aware Node Clustering (6G-NENC) framework, specifically designed to leverage 6G-native features such as adaptive spectrum utilization, AI-driven resource allocation, and real-time channel-state monitoring. The proposed approach incorporates a dynamic cluster-head selection mechanism based on instantaneous link quality and residual energy, coupled with link-adaptive and load-balanced data-forwarding strategies. These design choices ensure reduced end-to-end delay, improved reliability, and prolonged network lifetime, even in mobility-intensive IoHT environments. The framework’s performance is validated through extensive simulations under diverse network densities, traffic models, and channel conditions, and compared with several state-of-the-art protocols. Key performance indicators such as latency, packet delivery ratio (PDR), energy consumption, throughput, and Age-of-Information (AoI), consistently demonstrate that 6G-NENC delivers superior efficiency, robustness, and scalability. The results highlight its potential as a foundational architecture for next-generation IoHT systems requiring stringent quality-of-service and quality-of-experience guarantees.