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

Maximum Power Transfer01:16

Maximum Power Transfer

287
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...
287
Short-distance Transport of Resources02:12

Short-distance Transport of Resources

16.1K
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.
16.1K
Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

138
The maximum power flow for lossy transmission lines is derived using ABCD parameters in phasor form. These parameters create a matrix relationship between the sending-end and receiving-end voltages and currents, allowing the determination of the receiving-end current. This relationship facilitates calculating the complex power delivered to the receiving end, from which real and reactive power components are derived.
138
Transmission Line Design Considerations01:23

Transmission Line Design Considerations

166
Aluminum has become the material of choice for overhead transmission lines, surpassing copper due to its abundance and cost-effectiveness. The most prevalent type is the aluminum conductor, steel-reinforced (ACSR), which combines aluminum strands around a steel core. Other variants include all-aluminum conductors (AAC), all-aluminum alloy conductors (AAAC), aluminum conductor alloy-reinforced (ACAR), and aluminum-clad steel conductors. Advanced designs, such as aluminum conductors with steel...
166
Energy to Drive Translocation01:37

Energy to Drive Translocation

2.1K
Mitochondrial protein import is powered by two distinct energy sources: ATP hydrolysis and electrochemical potential across the inner membrane. Newly synthesized precursors are bound by cytosolic chaperones of the Hsp70 family, which guide them to the import receptors on the mitochondrial surface. Utilizing the energy of ATP hydrolysis, Hsp70 chaperones transfer these precursors to the TOM receptors on the mitochondrial outer membrane.
Generally, polypeptides are unfolded by two distinct...
2.1K
Energy and Power Signals01:17

Energy and Power Signals

338
In an electrical system with a resistor, voltage and current signals facilitate the measurement of power and energy across the resistor. For a continuous-time signal, the total energy over a time interval is defined as the integral of the square of the signal's magnitude over that interval. Mathematically, this is expressed as:
338

You might also read

Related Articles

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

Sort by
Same author

Organizational cronyism and employee psychological withdrawal behavior: the mediating role of disidentification and moderating effect of employability.

BMC psychology·2025
Same author

Facile Bond Exchanging Strategy for Engineering Wet Adhesion and Antioxidant/Antibacterial Thin Layer over a Dynamic Hydrogel via the Carbon Dots Derived from Tannic Acid/ε-Polylysine.

ACS applied materials & interfaces·2024
Same author

Recent Progress on Chiral Carbon Dots: Synthetic Strategies and Biomedical Applications.

ACS biomaterials science & engineering·2023
Same author

Antibacterial and antibiofilm mechanisms of carbon dots: a review.

Journal of materials chemistry. B·2023
Same author

HPS6 interacts with dynactin p150Glued to mediate retrograde trafficking and maturation of lysosomes.

Journal of cell science·2014
Same author

Intermittent hypothermia is neuroprotective in an in vitro model of ischemic stroke.

International journal of biological sciences·2014

Related Experiment Video

Updated: Jul 19, 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

604

Intelligent Resource Allocation for V2V Communication with Spectrum-Energy Efficiency Maximization.

Chunning Xu1, Shumo Wang2, Ping Song2

  • 1School of Architecture, Urban Planning & Design Institute, Southest University, Nanjing 210096, China.

Sensors (Basel, Switzerland)
|August 12, 2023
PubMed
Summary

This study introduces a new algorithm for vehicle-to-vehicle (V2V) communication resource allocation using multi-agent deep Q-networks (MDQN). It enhances spectrum-energy efficiency (SEE) for the Internet of Vehicles (IoV) network.

Keywords:
5G network slicingmulti-agent deep Q learningresource allocationvehicular networking

More Related Videos

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
Calibration of Vector Network Analyzer for Measurements in Radio Frequency Propagation Channels
10:00

Calibration of Vector Network Analyzer for Measurements in Radio Frequency Propagation Channels

Published on: June 2, 2020

21.1K

Related Experiment Videos

Last Updated: Jul 19, 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

604
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
Calibration of Vector Network Analyzer for Measurements in Radio Frequency Propagation Channels
10:00

Calibration of Vector Network Analyzer for Measurements in Radio Frequency Propagation Channels

Published on: June 2, 2020

21.1K

Area of Science:

  • Wireless communication
  • Network resource allocation
  • Artificial intelligence in networking

Background:

  • Traditional resource allocation algorithms struggle with the high reliability and low latency demands of vehicle-to-vehicle (V2V) communication in the Internet of Vehicles (IoV).
  • Existing methods often fail to optimize for both spectrum-energy efficiency (SEE) and critical communication constraints.

Purpose of the Study:

  • To propose a novel wireless resource allocation algorithm for V2V communication that addresses the limitations of traditional approaches.
  • To maximize the weighted spectrum-energy efficiency (SEE) within the constraints of ultra-low latency and high reliability.
  • To leverage 5G network slicing technology for enhanced IoV communication.

Main Methods:

  • A multi-agent deep Q-network (MDQN) based algorithm is developed, treating each V2V link as an independent agent.
  • The MDQN's state space, action set, and reward function are specifically designed for the V2V communication environment.
  • Centralized training of the MDQN is employed to determine optimal neural network parameters, enabling distributed execution of the resource allocation strategy.

Main Results:

  • The proposed MDQN-based algorithm significantly improves the overall spectrum-energy efficiency (SEE) of the IoV network.
  • The scheme effectively maintains a high success rate for V2V link load transmission, meeting reliability requirements.
  • Simulation results validate the algorithm's effectiveness in balancing SEE maximization with latency and reliability constraints.

Conclusions:

  • The developed MDQN algorithm offers a superior solution for wireless resource allocation in V2V communication compared to traditional methods.
  • The integration of 5G network slicing and MDQN provides an effective framework for optimizing IoV performance.
  • This approach demonstrates a viable strategy for meeting the demanding communication requirements of future autonomous vehicle networks.