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

15.2K
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...
15.2K
Sampling Plans01:23

Sampling Plans

1.1K
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...
1.1K
The Electrical Double Layer01:30

The Electrical Double Layer

15
In the region where two bulk phases meet, an intricate electric charge distribution arises due to charge transfer, ion adsorption, molecular orientation, and charge distortion. This complex distribution is commonly referred to as the electrical double layer.When a solid electrode interfaces with ions in an electrolyte solution, the speed of electron transfer dictates the rates of oxidation and reduction. The electrode acquires a charge through the escape of atoms into the solution as cations or...
15
Maximum Power Transfer01:16

Maximum Power Transfer

1.0K
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...
1.0K
Power Distribution in Three-phase and Single Phase Circuits01:17

Power Distribution in Three-phase and Single Phase Circuits

689
Power distribution within electrical circuits is a foundational aspect of residential and industrial energy systems. While single-phase power is common in residential settings, three-phase power is the standard for industrial environments with heavy machinery. Each system is different and has advantages, and it's crucial to understand the underlying principles of power distribution and material efficiency.
Single-Phase Power Distribution:
Single-phase circuits are typical in household settings;...
689
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

1.2K
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...
1.2K

You might also read

Related Articles

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

Sort by
Same author

An Analytical Framework for the IEEE 802.15.4 MAC Layer Protocol under Periodic Traffic.

Sensors (Basel, Switzerland)·2020
Same author

A Network Equivalent-Based Algorithm for Adaptive Parameter Tuning in 802.15.4 WSNs.

Sensors (Basel, Switzerland)·2018
Same author

Achieving Crossed Strong Barrier Coverage in Wireless Sensor Network.

Sensors (Basel, Switzerland)·2018
Same author

Vehicle autonomous localization in local area of coal mine tunnel based on vision sensors and ultrasonic sensors.

PloS one·2017
Same author

MB-OFDM-UWB Based Wireless Multimedia Sensor Networks for Underground Coalmine: A Survey.

Sensors (Basel, Switzerland)·2016
Same author

The Video Collaborative Localization of a Miner's Lamp Based on Wireless Multimedia Sensor Networks for Underground Coal Mines.

Sensors (Basel, Switzerland)·2015
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: Mar 3, 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

DCE: A Distributed Energy-Efficient Clustering Protocol for Wireless Sensor Network Based on Double-Phase Cluster-Head

Ruisong Han1, Wei Yang2, Yipeng Wang3

  • 1School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China. hanruisong@bjtu.edu.cn.

Sensors (Basel, Switzerland)
|May 5, 2017
PubMed
Summary
This summary is machine-generated.

A new protocol called DCE improves wireless sensor network (WSN) lifetime by efficiently electing energy-rich cluster heads. This distributed approach balances energy consumption for longer network stability.

Keywords:
clusteringdistributedenergy consumptionheterogeneouswireless sensor network

More Related Videos

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: Mar 3, 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
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:

  • Computer Science
  • Electrical Engineering
  • Network Engineering

Background:

  • Wireless Sensor Networks (WSNs) face challenges with energy consumption and limited lifetime.
  • Energy heterogeneity among nodes significantly impacts WSN performance and longevity.
  • Existing clustering protocols often do not adequately address energy disparities in WSNs.

Purpose of the Study:

  • To propose a novel distributed energy-efficient clustering protocol (DCE) for heterogeneous WSNs.
  • To enhance the lifetime and stability period of WSNs by considering energy heterogeneity.
  • To introduce a Double-phase Cluster-head Election scheme for improved energy distribution.

Main Methods:

  • Developed the DCE protocol with a two-phase cluster-head election mechanism.
  • Phase 1: Tentative cluster heads elected based on initial and residual energy levels.
  • Phase 2: Tentative heads replaced by members with higher residual energy to ensure optimal cluster head selection.

Main Results:

  • The DCE protocol ensures nodes with greater energy have a higher probability of becoming cluster heads.
  • Energy consumption is effectively distributed across the network.
  • Simulation results demonstrate DCE achieves longer stability periods compared to other protocols in heterogeneous WSNs.

Conclusions:

  • The proposed DCE protocol effectively manages energy heterogeneity in WSNs.
  • DCE significantly extends the network lifetime and stability period through its energy-aware clustering approach.
  • The Double-phase Cluster-head Election scheme is a viable strategy for energy-efficient WSNs.