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Dynamic Computation Offloading Scheme for Drone-Based Surveillance Systems.

Bongjae Kim1, Hong Min2, Junyoung Heo3

  • 1Division of Computer Science and Engineering, Sun Moon University, Asan 31460, Korea. bjkim@sunmoon.ac.kr.

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|September 12, 2018
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Summary
This summary is machine-generated.

This study introduces a mobility-aware dynamic computation offloading scheme for drone-based surveillance. The proposed method efficiently reduces response times for tracking moving objects by considering target dwell time and network failure rates.

Keywords:
droneoffloadingsurveillance

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Area of Science:

  • Computer Science
  • Robotics
  • Artificial Intelligence

Background:

  • Unmanned aerial vehicles (UAVs), including drones, are increasingly studied for various applications.
  • Drone-based mobile surveillance systems offer capabilities in object recognition and tracking.
  • Real-time object tracking and recognition are critical, time-sensitive tasks in surveillance.

Purpose of the Study:

  • To propose a mobility-aware dynamic computation offloading scheme for drone-based object tracking and recognition.
  • To reduce the time required for recognizing and tracking moving target objects.
  • To enhance the efficiency of drone surveillance systems for time-critical operations.

Main Methods:

  • Developed a dynamic computation offloading scheme tailored for mobile drones.
  • Incorporated drone mobility awareness into the offloading strategy.
  • Integrated considerations for moving target object dwell time and network failure rate into response time estimation.

Main Results:

  • The proposed scheme effectively reduces the response time for tracking moving objects.
  • Simulation results validate the efficiency of the mobility-aware dynamic computation offloading.
  • Accurate response time estimation is achieved by factoring in target dwell time and network failure rates.

Conclusions:

  • The mobility-aware dynamic computation offloading scheme significantly improves drone-based surveillance performance.
  • The method offers an efficient solution for time-critical object tracking and recognition tasks.
  • This approach enhances the practical applicability of drones in dynamic surveillance scenarios.