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

Multimachine Stability01:25

Multimachine Stability

163
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
163
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

56
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...
56
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

204
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:
204
Thevinin's Theorem01:15

Thevinin's Theorem

562
Thévenin's theorem plays a pivotal role in electrical circuit analysis, offering a solution to the challenges posed by variable loads within a circuit. In practical applications, it is common to encounter circuits where certain elements remain fixed while others fluctuate, often referred to as the "load." A typical household electrical outlet serves as a prime example of a variable load, as it can be connected to a variety of appliances, each with its own unique electrical...
562
Norton Equivalent Circuits01:16

Norton Equivalent Circuits

389
Norton's theorem is a fundamental concept in the field of electrical engineering that allows for the simplification of complex AC circuits. The theorem states that any two-terminal linear network can be replaced with an equivalent circuit that consists of an impedance, which is parallel with a constant current source. Figure 1 shows the AC circuit portioned into two parts: Circuit A and Circuit B, while Figure 2 depicts the circuit obtained by replacing Circuit A by its Norton equivalent...
389
Norton's Theorem01:14

Norton's Theorem

602
Norton's theorem is a fundamental principle stating that a linear two-terminal circuit can be substituted with an equivalent circuit, which comprises a current source (ⅠN) in parallel with a resistor (RN). Here, ⅠN represents the short-circuit current flowing through the terminals, and RN stands for the input or equivalent resistance at the terminals when all independent sources are deactivated. This implies that the circuit illustrated in Figure (a) can be exchanged with the...
602

You might also read

Related Articles

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

Sort by
Same author

Spatio-Temporal Heterogeneity-Oriented Graph Convolutional Network for Urban Traffic Flow Prediction.

Sensors (Basel, Switzerland)·2025
Same author

Sensor Management Method of Giving Priority to Confirmed Identified Targets.

Sensors (Basel, Switzerland)·2023
Same author

CAAGP: Rethinking channel attention with adaptive global pooling for liver tumor segmentation.

Computers in biology and medicine·2021
Same author

Joint resource optimization in spectrum sharing decode and forward relaying networks.

PloS one·2021
Same author

Joint Resource Optimization for Orthogonal Frequency Division Multiplexing Based Cognitive Amplify and Forward Relaying Networks.

Sensors (Basel, Switzerland)·2020
Same author

miR-200c/PAI-2 promotes the progression of triple negative breast cancer via M1/M2 polarization induction of macrophage.

International immunopharmacology·2019

Related Experiment Video

Updated: Jul 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

583

Computing Offloading Based on TD3 Algorithm in Cache-Assisted Vehicular NOMA-MEC Networks.

Tianqing Zhou1, Ming Xu1, Dong Qin2

  • 1School of Information Engineering, East China Jiaotong University, Nanchang 330013, China.

Sensors (Basel, Switzerland)
|November 25, 2023
PubMed
Summary
This summary is machine-generated.

This study minimizes vehicle energy consumption in mobile edge computing networks by combining non-orthogonal multiple access (NOMA) and mobile edge caching. The proposed TD3O algorithm and a heuristic algorithm (HA) effectively reduce energy usage compared to benchmarks.

Keywords:
MECNOMATD3computation offloadingedge cacheresource allocationvehicular networks

More Related Videos

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation
11:41

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation

Published on: February 1, 2020

20.4K
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

Related Experiment Videos

Last Updated: Jul 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

583
Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation
11:41

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation

Published on: February 1, 2020

20.4K
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

Area of Science:

  • Mobile Edge Computing (MEC)
  • Wireless Communication Networks
  • Resource Management

Background:

  • Mobile edge computing (MEC) networks face challenges in energy consumption and data transmission time.
  • Vehicular networks require efficient resource allocation and task offloading strategies.
  • Non-orthogonal multiple access (NOMA) and mobile edge caching are key technologies for enhancing MEC performance.

Purpose of the Study:

  • To minimize energy consumption for mobile devices (MDs) in cache-assisted vehicular NOMA-MEC networks.
  • To jointly optimize computing resource allocation, subchannel selection, device association, offloading, and caching decisions.
  • To address time and resource constraints in vehicular MEC environments.

Main Methods:

  • Formulation of an optimization problem to minimize vehicle energy consumption.
  • Development of a joint computation offloading and task-caching algorithm based on the twin-delayed deep deterministic policy gradient (TD3) algorithm (TD3O).
  • Design of an effective heuristic algorithm (HA) for non-iterative problem-solving.
  • Inclusion of an action transformation (AT) algorithm to convert continuous action space to discrete.

Main Results:

  • The TD3O algorithm demonstrated lower local energy consumption compared to several benchmark algorithms.
  • The heuristic algorithm (HA) achieved lower energy consumption than completely offloading and local execution algorithms.
  • Detailed analyses of computation complexity and convergence were provided.

Conclusions:

  • The proposed TD3O and HA algorithms offer effective solutions for reducing energy consumption in vehicular NOMA-MEC networks.
  • Joint optimization of offloading and caching decisions is crucial for energy efficiency.
  • The developed algorithms provide practical insights for future MEC system design.