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 Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

156
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.
156
Importance of Energy Conservation01:15

Importance of Energy Conservation

Importance of Energy ConservationEnergy conservation means using energy wisely and reducing unnecessary energy use. It helps save natural resources, lowers pollution, and reduces energy bills. Conserving energy is important for protecting the environment and ensuring that future generations can access the energy they need. Every action counts, whether it's turning off lights when they're not in use or selecting energy-efficient appliances. These small choices can have a significant...
Distribution Reliability and Automation01:25

Distribution Reliability and Automation

144
Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
144
Energy Conservation and Bernoulli's Equation01:16

Energy Conservation and Bernoulli's Equation

9.0K
Applying the conservation of energy principle or the work-energy theorem to an incompressible, inviscid fluid in laminar, steady, irrotational flow leads to Bernoulli's equation. It states that the sum of the fluid pressure, potential, and kinetic energy per unit volume is constant along a streamline.
All the terms in the equation have the dimension of energy per unit volume. The kinetic energy per unit volume is called the kinetic energy density, and the potential energy per unit volume is...
9.0K
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
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

692
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...
692

You might also read

Related Articles

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

Sort by
Same author

Targeted metabolomics analysis for discriminating geographical origin of Chardonnay grape and wine at sub-regions in China's Ningxia: Terroir effect.

Food research international (Ottawa, Ont.)·2026
Same author

Phase-Pure Quasi-Two-Dimensional Layered Perovskites Enable Efficient Blue Light-Emitting Diodes.

Nano letters·2025
Same author

Tailored large-particle quantum dots with high color purity and excellent electroluminescent efficiency.

Science bulletin·2025
Same author

Precision and Robust Models on Healthcare Institution Federated Learning for Predicting HCC on Portal Venous CT Images.

IEEE journal of biomedical and health informatics·2024
Same author

Enhancing Light Outcoupling Efficiency via Anisotropic Low Refractive Index Electron Transporting Materials for Efficient Perovskite Light-Emitting Diodes.

Advanced materials (Deerfield Beach, Fla.)·2024
Same author

Recurrent Neural Network Methods for Extracting Dynamic Balance Variables during Gait from a Single Inertial Measurement Unit.

Sensors (Basel, Switzerland)·2023

Related Experiment Video

Updated: Aug 13, 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

632

A Near-Optimal Energy Management Mechanism Considering QoS and Fairness Requirements in Tree Structure Wireless

Kuang-Yen Tai1, Bo-Chen Liu1, Chiu-Han Hsiao2

  • 1Department of Information Management, National Taiwan University, Taibei 106, Taiwan.

Sensors (Basel, Switzerland)
|January 21, 2023
PubMed
Summary

This study optimizes energy consumption in AIoT wireless sensor networks by modeling network efficiency and fairness. The Lagrangian Relaxation method minimizes power usage while maintaining high transmission efficiency.

Keywords:
Lagrangian RelaxationQoSenergy consumptionsensor activitywireless sensor network

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

3.8K
In Situ Soil Moisture Sensors in Undisturbed Soils
08:20

In Situ Soil Moisture Sensors in Undisturbed Soils

Published on: November 18, 2022

6.4K

Related Experiment Videos

Last Updated: Aug 13, 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

632
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
In Situ Soil Moisture Sensors in Undisturbed Soils
08:20

In Situ Soil Moisture Sensors in Undisturbed Soils

Published on: November 18, 2022

6.4K

Area of Science:

  • Artificial Intelligence of Things (AIoT)
  • Wireless Sensor Networks (WSNs)

Background:

  • AIoT technologies enable real-time sensing and widespread WSN deployment.
  • Limited power and wireless data transmission in WSNs create significant energy consumption challenges.
  • Efficient energy management is crucial for practical WSN applications.

Purpose of the Study:

  • To develop a mathematical model for tree-structured WSNs addressing Quality of Service (QoS) and fairness.
  • To minimize energy consumption in WSNs by optimizing sensor activity, transmission distance, and packet size.
  • To enhance the overall efficiency of WSNs in AIoT environments.

Main Methods:

  • Constructed a tree-structure wireless sensor network mathematical model.
  • Incorporated QoS and fairness requirements into the model.
  • Utilized the Lagrangian Relaxation method to find optimal solutions for energy minimization.

Main Results:

  • Achieved significant improvements in decision-making speed.
  • Demonstrated effective reduction in energy consumption.
  • Maintained network transmission efficiency while minimizing power usage.

Conclusions:

  • The proposed model and method effectively address energy consumption challenges in AIoT WSNs.
  • Optimized WSN parameters lead to enhanced operational efficiency and extended network lifetime.
  • The study provides a viable solution for practical, energy-efficient WSN deployments.