Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

746
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
746
Distributed Loads01:19

Distributed Loads

635
Distributed loads are a common type of load that engineers and scientists encounter in various practical situations. Distributed loads often refer to a type of load spread over a surface or a structure and can be modeled as continuous force per unit area.
For example, consider a bookshelf filled with books stacked vertically adjacent to each other. The weight of the books is evenly distributed over the length of the shelf. As a result, the pressure at different locations on the surface of the...
635
Short-distance Transport of Resources02:12

Short-distance Transport of Resources

16.5K
Short-distance transport refers to transport that occurs over a distance of just 2-3 cells, crossing the plasma membrane in the process. Small uncharged molecules, such as oxygen, carbon dioxide, and water, can diffuse across the plasma membrane on their own. In contrast, ions and larger molecules require the assistance of transport proteins due to their charge or size. Transport across membranes also occurs within individual cells, playing a variety of essential roles for the plant as a whole.
16.5K
Absolute Motion Analysis- General Plane Motion01:24

Absolute Motion Analysis- General Plane Motion

278
Visualize a drone, with its propellers spinning rapidly, hovering mid-air. The fascinating movements and operations of this drone can be comprehended by applying the principle of general plane motion.
As the drone's propellers rotate, an upward force is generated that counteracts the force of gravity, enabling the drone to lift off from the ground. This initial movement of the drone is along a straight path, representing a form of translational motion. In this phase, every point on the...
278
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

305
The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
305
Maximum Power Transfer01:16

Maximum Power Transfer

430
Numerous practical applications within engineering disciplines, such as telecommunications, necessitate optimizing power delivery to a connected load. This pursuit, however, entails inherent internal losses, which can either equal or exceed the power supplied to the load. The Thevenin equivalent circuit is helpful in finding the maximum power a linear circuit can deliver to a load. It is assumed in this context that the load resistance can be adjusted.
By substituting the entire circuit with...
430

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Distribution characteristics and influencing factors of three-dimensional lens parameters in patients with age-related cataracts.

BMC ophthalmology·2026
Same author

Disrupted brain functional networks in adolescents and young adults with gaming disorder during social interaction: An fNIRS study.

Psychological medicine·2026
Same author

Synergy Between Ru<sub>3</sub> Nanoclusters and Pt Nanoparticles for High-Efficiency Alkaline Hydrogen Evolution Reaction.

Angewandte Chemie (International ed. in English)·2026
Same author

Low-latency FPGA-based TDC phase detection scheme for optical frequency comb locking.

Optics letters·2026
Same author

The characteristics of collagen-induced rheumatoid arthritis in macaques and the changes of heart.

Animal models and experimental medicine·2026
Same author

Atypical contributions of reward decisions to momentary mood in individuals with methamphetamine use disorder.

BMC psychiatry·2025
Same journal

Research on a Regional Availability Evaluation Model for Road-Area High-Entropy Energy Based on Synergy Factors.

Entropy (Basel, Switzerland)·2026
Same journal

Atmospheric Turbulence Channel Modeling and Performance Analysis of a CO-ZP-OFDM Coherent Optical Communication System for UAV Air-to-Ground Scenarios.

Entropy (Basel, Switzerland)·2026
Same journal

Information Geometry and Asymptotic Theory for SMML Estimators.

Entropy (Basel, Switzerland)·2026
Same journal

Correlation Entropy and Power-Law Kinetics.

Entropy (Basel, Switzerland)·2026
Same journal

Research on the Contagion of Systemic Financial Risk Under the Impact of Climate Risks-From the Perspective of Complex Networks and Machine Learning.

Entropy (Basel, Switzerland)·2026
Same journal

The Statistical-Mechanical Meaning of the Wave Function of Quantum Mechanics.

Entropy (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Sep 21, 2025

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization
07:49

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization

Published on: November 26, 2019

8.2K

Task Offloading Strategy Based on Mobile Edge Computing in UAV Network.

Wei Qi1, Hao Sun2, Lichen Yu3

  • 1Department of Information Technology, Jiangsu Union Technical Institute, Xuzhou 221000, China.

Entropy (Basel, Switzerland)
|May 28, 2022
PubMed
Summary
This summary is machine-generated.

This study proposes a mobile edge computing offloading strategy using reinforcement learning for unmanned aerial vehicles (UAVs). The method enhances UAV efficiency by offloading tasks to edge servers, improving overall operational revenue.

Keywords:
mobile edge computingstackelberg gameunmanned aerial vehicle

More Related Videos

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem
10:15

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem

Published on: February 3, 2021

3.9K
Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

672

Related Experiment Videos

Last Updated: Sep 21, 2025

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization
07:49

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization

Published on: November 26, 2019

8.2K
Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem
10:15

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem

Published on: February 3, 2021

3.9K
Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

672

Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Robotics

Background:

  • Unmanned aerial vehicles (UAVs) face limitations in computing capacity and battery power for complex tasks.
  • Offloading tasks to edge servers can enhance UAV efficiency and operational capabilities.

Purpose of the Study:

  • To propose a mobile edge computing (MEC) offloading strategy for UAVs based on reinforcement learning.
  • To optimize task offloading for computationally intensive and real-time operations.

Main Methods:

  • Introduced a Stackelberg game model to represent UAVs and edge nodes.
  • Utilized a utility function for maximizing offloading revenue.
  • Applied the multi-agent deep deterministic policy gradient (MADDPG) algorithm to solve the mixed-integer non-linear programming (MINLP) problem.

Main Results:

  • Simulations demonstrated the effectiveness of the proposed algorithm.
  • Evaluated the impact of the number of UAVs and available computing resources on total revenue.
  • The proposed algorithm showed superior performance compared to other existing algorithms.

Conclusions:

  • The reinforcement learning-based MEC offloading strategy significantly improves the total revenue of UAVs.
  • The approach effectively addresses the computational and power limitations of UAVs in complex missions.