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An Energy Efficient UAV-Based Edge Computing System with Reliability Guarantee for Mobile Ground Nodes.

Seung-Yeon Kim1, Yi-Kang Kim1

  • 1Department of Computer Convergence Software, Korea University, Sejong 30019, Korea.

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Summary
This summary is machine-generated.

This study introduces an energy-efficient unmanned aerial vehicle (UAV)-based edge computing system with energy harvesting. The system enhances reliability and efficiency for mobile ground nodes (MGN) by optimizing UAV task allocation.

Keywords:
edge computingenergy efficiencymobile ground node (MGN)reliabilityunmanned aerial vehicle (UAV)

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Robotics

Background:

  • Edge computing systems offer distributed computation and storage near end-users.
  • Unmanned Aerial Vehicle (UAV)-aided edge computing provides flexible mobile ground node (MGN) configurations.
  • Current systems face challenges in guaranteed reliability and efficient energy management.

Purpose of the Study:

  • To propose an energy-efficient UAV-based edge computing system with energy harvesting capabilities.
  • To address the need for higher reliability and improved energy management in UAV-assisted edge computing.
  • To optimize the performance of mobile ground nodes (MGN) utilizing distributed UAV resources.

Main Methods:

  • Developed a distributed data processing framework where proximate UAVs collaborate.
  • Formulated a stochastic game model with constraints to minimize UAV energy consumption.
  • Applied a best response algorithm to find a multi-policy constrained Nash equilibrium.

Main Results:

  • The proposed system demonstrates improved lifecycle compared to individual computing schemes.
  • Achieved a sufficient probability of successful computation completion.
  • The energy-efficient design balances computational demands with energy harvesting.

Conclusions:

  • The UAV-based edge computing system effectively enhances reliability and energy efficiency.
  • The stochastic game model provides a robust framework for optimizing distributed UAV resources.
  • This approach paves the way for more widespread adoption of UAV-assisted edge computing solutions.