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Trajectory-Aware Offloading Decision in UAV-Aided Edge Computing: A Comprehensive Survey.

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  • 1Department of Computer Engineering, Chosun University, 309 Pilmun-daero, Dong-gu, Gwangju 61452, Republic of Korea.

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Summary
This summary is machine-generated.

This survey reviews trajectory-aware offloading decisions for Unmanned Aerial Vehicle (UAV) aided edge computing. Optimizing UAV paths is crucial for efficient computation offloading in Internet of Things (IoT) systems.

Keywords:
UAV-aided edge computingmobile edge computingoffloading decisiontask offloadingtrajectory planningunmanned aerial vehicle

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Robotics

Background:

  • Unmanned Aerial Vehicles (UAVs) integrated with edge computing offer vital support for Internet of Things (IoT) applications in remote and challenging environments.
  • Effective offloading decisions are critical for optimizing system performance in UAV-aided edge computing.

Purpose of the Study:

  • To survey and analyze existing trajectory-aware offloading decision techniques for UAV-aided edge computing.
  • To provide a comprehensive overview of design concepts, operational features, and characteristics of these techniques.

Main Methods:

  • Review of current literature on trajectory-aware offloading decision techniques.
  • Comparative analysis of techniques based on design principles and operational characteristics.

Main Results:

  • Identified and categorized various trajectory-aware offloading strategies.
  • Highlighted the significant impact of UAV trajectory on offloading decisions and overall system performance.

Conclusions:

  • Trajectory optimization is a key factor in enhancing UAV-aided edge computing for IoT.
  • Further research is needed to address open issues and explore future directions in this domain.