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

689
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...
689
Distributed Loads01:19

Distributed Loads

575
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...
575
Parallel Processing01:20

Parallel Processing

196
The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
196
Short-distance Transport of Resources02:12

Short-distance Transport of Resources

16.3K
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.
16.3K
Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

700
A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of...
700
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

90
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
90

You might also read

Related Articles

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

Sort by
Same author

Computation Offloading Game for Multi-Channel Wireless Sensor Networks.

Sensors (Basel, Switzerland)·2022
Same author

[Experience of recording NMDA current in brain slices by whole-cell patch clamp technique].

Zhongguo ying yong sheng li xue za zhi = Zhongguo yingyong shenglixue zazhi = Chinese journal of applied physiology·2021
Same author

Association of LncRNA-GAS5 gene polymorphisms and PBMC LncRNA-GAS5 level with risk of systemic lupus erythematosus in Chinese population.

Journal of cellular and molecular medicine·2021
See all related articles

Related Experiment Video

Updated: Aug 10, 2025

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

628

Computation Offloading and User-Clustering Game in Multi-Channel Cellular Networks for Mobile Edge Computing.

Yan-Yun Huang1, Pi-Chung Wang1

  • 1Department of Computer Science and Engineering, National Chung Hsing University, Taichung 402, Taiwan.

Sensors (Basel, Switzerland)
|February 11, 2023
PubMed
Summary

This study introduces a distributed algorithm for mobile edge computing that optimizes device clustering and computation offloading. The novel approach enhances transmission efficiency, reducing energy consumption and improving application responsiveness for mobile devices.

Keywords:
Nash equilibriumclusteringcomputation offloadinggame theorymobile edge computing

More Related Videos

The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

9.4K
Finite Element Modelling of a Cellular Electric Microenvironment
08:23

Finite Element Modelling of a Cellular Electric Microenvironment

Published on: May 18, 2021

3.5K

Related Experiment Videos

Last Updated: Aug 10, 2025

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

628
The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

9.4K
Finite Element Modelling of a Cellular Electric Microenvironment
08:23

Finite Element Modelling of a Cellular Electric Microenvironment

Published on: May 18, 2021

3.5K

Area of Science:

  • Computer Science
  • Electrical Engineering
  • Telecommunications

Background:

  • Mobile devices utilize mobile edge computing (MEC) for enhanced energy efficiency and responsiveness via computation offloading.
  • Device transmissions in MEC can cause interference, degrading upload rates and increasing transmission delays.
  • Existing clustering methods lack distributed algorithms for optimizing both clustering and computation offloading.

Purpose of the Study:

  • To develop a distributed algorithm for optimizing computation offloading in mobile edge computing.
  • To minimize mobile device energy consumption by adaptively clustering devices and improving transmission efficiency.
  • To address the challenge of interference and transmission delay in dense mobile device environments.

Main Methods:

  • Formulated the distributed optimization problem of clustering and computation offloading as a potential game.
  • Constructed the potential game and demonstrated the existence of a Nash equilibrium.
  • Proposed a novel distributed algorithm for adaptive clustering and computation offloading based on game theory.

Main Results:

  • Simulations confirmed the proposed algorithm's effectiveness in improving offloading efficiency for mobile devices in MEC.
  • The algorithm successfully enhanced transmission efficiency, leading to reduced energy consumption.
  • Simultaneous improvements in mobile device energy efficiency and application responsiveness were observed.

Conclusions:

  • The developed distributed algorithm offers an effective solution for optimizing computation offloading in mobile edge computing.
  • Adaptive clustering and game-theoretic approaches can mitigate interference and enhance transmission efficiency.
  • The findings contribute to more energy-efficient and responsive mobile edge computing systems.