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<p>Software-defined VANET–IoT networks require adaptive, energy-aware routing to manage dynamic topology, high mobility, and heterogeneous traffic while maintaining scalability and quality of service. Conventional method routing incur computational overhead, sensitivity to parameter tuning, and reduced robustness under extreme mobility or large-scale, highly congested network scenarios. The increasing number of wireless devices in current time applications of the Internet of Things (IoT) creates difficulties such as reliability, scalability, and heterogeneity. A novel architecture, proposed a Software-Defined Vehicular Ad Hoc Network with IoT (SDVANET-IoT). Nonetheless, this strategy faces energy supply limits, intrusion detection, unexpected network dynamics, and service quality requirements. To address these issues, this research proposes an intelligent, energy-cognitive optimal harmony search optimization (ECOHSO) for SDVANET-IoT environments. The protocol aims to optimize energy consumption and detect threats in IoT networks while demonstrating adaptability to network changes. The strategy evaluates the relevant objectives and designs routing mechanisms that balance energy efficiency with other key performance metrics. Statistical analysis using a paired t-test was performed to confirm the significance of performance improvements. Extensive simulations reveal significant improvements in packet delivery ratio and data delivery latency as compared to conventional approaches.</p>

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An Energy-Efficient ECOHSO-Based Routing Framework for Software-Defined VANET-IoT Networks

  • 期刊论文

  • 发表日期：

    2026年2月16日

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  • Arvind Kumar Pandey,
  • Kumud Saxena,
  • K. V Manjunath,
  • Praveen Priyaranjan Nayak,
  • Veera Nagaiah Maddikayala

摘要

Software-defined VANET–IoT networks require adaptive, energy-aware routing to manage dynamic topology, high mobility, and heterogeneous traffic while maintaining scalability and quality of service. Conventional method routing incur computational overhead, sensitivity to parameter tuning, and reduced robustness under extreme mobility or large-scale, highly congested network scenarios. The increasing number of wireless devices in current time applications of the Internet of Things (IoT) creates difficulties such as reliability, scalability, and heterogeneity. A novel architecture, proposed a Software-Defined Vehicular Ad Hoc Network with IoT (SDVANET-IoT). Nonetheless, this strategy faces energy supply limits, intrusion detection, unexpected network dynamics, and service quality requirements. To address these issues, this research proposes an intelligent, energy-cognitive optimal harmony search optimization (ECOHSO) for SDVANET-IoT environments. The protocol aims to optimize energy consumption and detect threats in IoT networks while demonstrating adaptability to network changes. The strategy evaluates the relevant objectives and designs routing mechanisms that balance energy efficiency with other key performance metrics. Statistical analysis using a paired t-test was performed to confirm the significance of performance improvements. Extensive simulations reveal significant improvements in packet delivery ratio and data delivery latency as compared to conventional approaches.