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Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization
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An Energy Efficient Design of Computation Offloading Enabled by UAV.

Linpei Li1,2,3, Xiangming Wen1,2,3, Zhaoming Lu1,2,3

  • 1School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China.

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Summary

This study optimizes unmanned aerial vehicle (UAV) energy efficiency for mobile edge computing (MEC) services. The proposed scheme enhances offloading performance, especially in disaster areas with damaged infrastructure.

Keywords:
energy efficiency.mobile edge computingoffloadingunmanned aerial vehicle

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Area of Science:

  • Wireless Communication and Networking
  • Mobile Edge Computing
  • Aerial Robotics

Background:

  • Exploding data volumes necessitate advanced wireless systems like 5G.
  • Mobile Edge Computing (MEC) addresses computation and latency challenges.
  • Unmanned Aerial Vehicles (UAVs) offer agile deployment for MEC in communication-demand areas.

Purpose of the Study:

  • To design an energy-efficient scheme for UAV-enabled MEC services.
  • To address incomplete services due to UAV endurance limitations.
  • To provide high-quality offloading for users in areas with overloaded or damaged infrastructure.

Main Methods:

  • Developed an energy-efficient UAV design model considering energy, data causality, and speed constraints.
  • Jointly optimized UAV trajectory and bit allocation for maximum energy efficiency.
  • Employed a successive convex approximation-based alternating algorithm for non-convex optimization.

Main Results:

  • The proposed energy-efficient scheme significantly outperforms benchmark schemes.
  • Simulation results validate the effectiveness of the joint optimization approach.
  • Performance variations under different parameters were analyzed.

Conclusions:

  • The developed energy-efficient scheme enhances UAV-enabled MEC service quality.
  • The approach is particularly beneficial for disaster-stricken areas.
  • Optimized UAV trajectory and bit allocation are key to maximizing energy efficiency.