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

Cluster Sampling Method01:20

Cluster Sampling Method

14.9K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
14.9K
Sampling Plans01:23

Sampling Plans

1.0K
Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
1.0K
Survival Tree01:19

Survival Tree

440
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
440
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

1.1K
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...
1.1K
Uniform Depth Channel Flow: Problem Solving01:18

Uniform Depth Channel Flow: Problem Solving

532
To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
532

You might also read

Related Articles

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

Sort by
Same author

Robotic-assisted bronchoscopy-guided cryobiopsy for the diagnosis of ground-glass opacity-predominant peripheral pulmonary nodules.

Respiratory research·2026
Same author

Impact of Human Activities and Climate Change on Chinese Forest Musk Deer (<i>Moschus berezovskii</i>).

Biology·2026
Same author

Safety and efficacy of transbronchial radiofrequency ablation for stage IA peripheral lung cancer: a retrospective cohort study.

Translational lung cancer research·2025
Same author

A Hybrid State/Disturbance Observer-Based Feedback Control of Robot with Multiple Constraints.

Sensors (Basel, Switzerland)·2022
Same author

The preparation and electrochemical properties of Nd<sub>0.6</sub>Sr<sub>0.4</sub>Fe<sub>1-</sub>Zn<sub></sub>O<sub>3-</sub> cathode materials for intermediate temperature solid oxide fuel cells.

Physical chemistry chemical physics : PCCP·2022
Same author

Application of Microspectral Imaging in Motor and Sensory Nerve Classification.

Journal of healthcare engineering·2021
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Feb 18, 2026

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

1.2K

FTUC: A Flooding Tree Uneven Clustering Protocol for a Wireless Sensor Network.

Wei He1,2, Sebastien Pillement3, Du Xu4

  • 1School of Information Engineering, Guang Dong University of Technology, Guangzhou 510000, China. hewei2016@foxmail.com.

Sensors (Basel, Switzerland)
|November 24, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces a Flooding Tree Uneven Clustering (FTUC) protocol for wireless sensor networks (WSNs). FTUC effectively reduces energy consumption and balances node power, significantly extending network lifetime by addressing cluster head distribution and long-distance communication issues.

Keywords:
flooding treenetworkunequal clusteruneven clusteringwireless sensor network (WSN)

More Related Videos

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring
08:16

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring

Published on: October 24, 2025

666
Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles
11:54

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Published on: March 13, 2017

9.9K

Related Experiment Videos

Last Updated: Feb 18, 2026

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

1.2K
Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring
08:16

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring

Published on: October 24, 2025

666
Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles
11:54

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Published on: March 13, 2017

9.9K

Area of Science:

  • Wireless Sensor Networks (WSNs)
  • Network Protocols
  • Energy Efficiency

Background:

  • Clustering in WSNs reduces energy consumption but faces long-distance communication and premature node death (hot zones) issues.
  • Existing unequal clustering algorithms often result in uneven cluster head distribution and require complex global distance calculations.
  • These limitations hinder the scalability and efficiency of WSNs.

Purpose of the Study:

  • To propose a novel Flooding Tree Uneven Clustering (FTUC) protocol designed for large-scale wireless sensor networks.
  • To address the challenges of uneven cluster head distribution and the hot zones problem.
  • To enhance energy efficiency and prolong the operational lifetime of WSNs.

Main Methods:

  • FTUC constructs a tree-based sub-network to determine minimum and maximum distances for applying unequal cluster theory.
  • It utilizes referenced position circles for even election of cluster heads based on residual energy and distance.
  • A cluster head cost function is employed to optimize inter-cluster communication routes to the base station (BS).

Main Results:

  • FTUC demonstrates a significant decrease in overall node energy consumption.
  • The protocol effectively balances energy consumption across all nodes in the network.
  • Simulation results confirm that FTUC successfully extends the overall lifetime of the wireless sensor network.

Conclusions:

  • The proposed FTUC protocol offers an efficient solution for energy management in large WSNs.
  • By optimizing cluster head selection and routing, FTUC mitigates the hot zones problem and enhances network longevity.
  • FTUC provides a scalable and effective approach to prolonging WSN operational lifespan.