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Related Experiment Video

Updated: Jan 7, 2026

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization
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Energy-Aware adaptive virtualization and migration protocol for green IoT wireless sensor networks.

Yi Liu1, Yan Li1, Nianming Ge2

  • 1School of Electronic Information Engineering, Sanjiang University, Nanjing, 210000, Jiangsu Province, China.

Scientific Reports
|December 29, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces the Energy-Aware Adaptive Virtualization and Migration (EAVM) protocol for Green Internet of Things (IoT) wireless sensor networks. EAVM enhances energy efficiency and network stability through intelligent resource management and adaptive migration strategies.

Keywords:
Energy-AwareFederal deep reinforcement learning (FDRL)Green IoTResource migrationVirtualizationWireless sensor networks (WSN)

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Sustainability Science

Background:

  • The rapid growth of the Internet of Things (IoT) presents significant energy consumption and sustainability challenges in wireless sensor networks.
  • Existing solutions often struggle with dynamic energy fluctuations and efficient resource allocation in Green IoT environments.

Purpose of the Study:

  • To propose and evaluate the Energy-Aware Adaptive Virtualization and Migration (EAVM) protocol for Green IoT Wireless Sensor Networks.
  • To address energy requirements and sustainability issues through intelligent resource management.

Main Methods:

  • The EAVM protocol integrates Federated Deep Reinforcement Learning (FDRL) with hybrid solar-RF energy harvesting.
  • It dynamically allocates and migrates virtual resources based on real-time energy availability.
  • Performance is assessed via simulation against state-of-the-art techniques.

Main Results:

  • EAVM demonstrates superior energy efficiency compared to existing methods.
  • The protocol ensures effective workload balancing and enhances network stability.
  • Improved scalability is observed in dynamic IoT system simulations.

Conclusions:

  • EAVM offers a viable solution for sustainable resource management in Green IoT networks.
  • The protocol effectively balances energy consumption, performance, and network longevity.
  • This approach contributes to more sustainable and efficient IoT ecosystems.