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

647
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...
647
Absolute Motion Analysis- General Plane Motion01:24

Absolute Motion Analysis- General Plane Motion

224
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...
224
Manipulation and Analysis01:21

Manipulation and Analysis

26
GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
26
Field Application of Global Positioning System01:28

Field Application of Global Positioning System

48
The Global Positioning System (GPS) has become an indispensable tool in fieldwork, offering unparalleled precision and efficiency for surveying, navigation, and infrastructure development. By harnessing signals from a constellation of satellites, GPS receivers determine the location of objects with remarkable speed and accuracy, often completing calculations within a second.Advantages of Modern GPS TechnologyContemporary GPS receivers are designed to meet the practical demands of field...
48

You might also read

Related Articles

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

Sort by
Same author

Development and validation of pathomics signature for predicting prognosis of advanced high-grade serous ovarian carcinoma patients after platinum-based chemotherapy.

Scientific reports·2026
Same author

Joint effects of dyslipidemia and the platelet count on stroke risk: Longitudinal analysis via dynamic lipid stratification in the CHARLS cohort.

BMC neurology·2026
Same author

Age-related changes in multisensory emotional speech perception: Evidence for a dual-pathway model.

Psychology and aging·2026
Same author

Missed opportunities: Verbal backchannels and response behaviour at opportunity points in five-year-old English children with a history of late talking.

Journal of child language·2026
Same author

Restoring auditory discrimination in noise: mismatch negativity evidence for a deep neural network-based denoising system in hearing aids.

Hearing research·2026
Same author

Prioritization of self-associated voices is enhanced by positive prosodic valence: Roles of individual explicit self-esteem in self-bias and positive self-bias.

Consciousness and cognition·2026

Related Experiment Video

Updated: Jul 7, 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

8.1K

Analysis and prediction of UAV-assisted mobile edge computing systems.

Xiong Wang1, Zhijun Yang1,2,3, Hongwei Ding1

  • 1School of Information Science and Engineering, Yunnan University, Kunming, China.

Mathematical Biosciences and Engineering : MBE
|December 21, 2023
PubMed
Summary

This study integrates back propagation neural networks with mobile edge computing (MEC) for optimized task scheduling. The drone-assisted MEC model significantly reduces latency and queue length, enhancing network performance for the Internet of Things (IoT).

Keywords:
UAVapplied numerical methodsmachine learningmobile edge computingneural networkpartial-differential equationspolling system

More Related Videos

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

1.4K
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

3.8K

Related Experiment Videos

Last Updated: Jul 7, 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

8.1K
Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

1.4K
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

3.8K

Area of Science:

  • Computer Science
  • Network Engineering
  • Artificial Intelligence

Background:

  • Growing demand for Internet of Things (IoT) necessitates low-latency networks.
  • Mobile Edge Computing (MEC) offers a solution by offloading computation to edge servers.
  • Existing MEC models face challenges in optimizing task scheduling and processing.

Purpose of the Study:

  • To integrate Back Propagation (BP) neural networks with MEC for enhanced network performance.
  • To develop a drone-assisted MEC model for optimizing task scheduling and processing.
  • To address network challenges including latency, speed, and throughput.

Main Methods:

  • Introduced a drone-assisted MEC model with synchronous and asynchronous computation offloading modes.
  • Utilized Markov chains and probability-generation functions for synchronous mode parameter computation.
  • Developed a BP neural network to calculate average queue length and latency in asynchronous mode.

Main Results:

  • BP neural network results closely matched theoretical values from probability-generation functions.
  • The proposed UAV-assisted MEC model demonstrated superior performance compared to the synchronous mode.
  • Achieved significant reductions in latency (approx. 11.72%) and queue length (approx. 9.45%).

Conclusions:

  • The fusion of BP neural networks and MEC effectively optimizes task scheduling and processing.
  • The drone-assisted MEC approach significantly enhances network speed, reduces latency, and improves throughput.
  • This model provides a viable solution for low-latency network demands in IoT applications.