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Related Concept Videos

Cluster Sampling Method01:20

Cluster Sampling Method

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...
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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

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...
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

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...
Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
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Applications of EMF Measurements01:26

Applications of EMF Measurements

Electromotive force (EMF) measurements have a broad range of applications in various fields, including chemistry and physics. The electrochemical series, an arrangement of elements in order of their standard electrode potentials, can be determined through EMF measurements. Elements with lower standard potentials can reduce ions of elements with higher standard potentials.The standard cell potential, E°, allows for the calculation of the standard reaction Gibbs energy, ΔG°, and the equilibrium...
Inclusive Fitness00:57

Inclusive Fitness

Most altruistic behavior—in which one animal helps another at a cost to themselves—occurs between relatives. Scientists think these altruistic behaviors evolved because they increase the inclusive fitness of the animal providing help.

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Related Experiment Video

Updated: May 24, 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

CoCMA: Energy-Efficient Coverage Control in Cluster-Based Wireless Sensor Networks Using a Memetic Algorithm.

Joe-Air Jiang1, Chia-Pang Chen, Cheng-Long Chuang

  • 1Department of Bio-Industrial Mechatronics Engineering, National Taiwan University, Taipei 106, Taiwan; E-Mails: supercjb@pie.com.tw (C.C.); clchuang@ieee.org (C.C.); r96631025@ntu.edu.tw (T.L.).

Sensors (Basel, Switzerland)
|March 13, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces CoCMA, an energy-efficient coverage control for wireless sensor networks (WSNs). CoCMA prolongs network lifetime and maintains sensing coverage by optimizing node schedules and employing a smart wake-up scheme.

Keywords:
energy efficiencymemetic algorithmsensing coveragewireless sensor network

Related Experiment Videos

Last Updated: May 24, 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

Area of Science:

  • Computer Science
  • Wireless Sensor Networks
  • Network Optimization

Background:

  • Wireless sensor networks (WSNs) face energy limitations, necessitating energy-efficient designs.
  • Network coverage degrades over time, impacting the quality of service (QoS) for mission-critical applications.
  • Existing coverage control strategies struggle with energy conservation conflicts and suboptimal node wake-up schemes.

Purpose of the Study:

  • To implement an energy-efficient coverage control for cluster-based WSNs.
  • To address challenges in energy conservation and coverage preservation.
  • To prolong network lifetime while maintaining essential sensing capabilities.

Main Methods:

  • A novel approach named CoCMA (Coverage Control using Memetic Algorithm) is proposed.
  • CoCMA integrates a Memetic Algorithm (MA)-based schedule for sensor nodes to minimize redundant energy consumption.
  • A dynamic wake-up scheme is employed to recover coverage holes caused by node failures.

Main Results:

  • CoCMA effectively prolongs network lifetime and preserves sensing coverage in cluster-based WSNs.
  • Performance evaluations demonstrate superior results compared to existing approaches under various deployment scenarios.
  • The proposed method activates fewer sensor nodes to monitor the required sensing area, enhancing energy efficiency.

Conclusions:

  • The CoCMA approach offers a robust solution for energy-efficient coverage control in WSNs.
  • Combining MA-based scheduling with an intelligent wake-up scheme significantly improves network longevity and QoS.
  • CoCMA provides a practical method for optimizing resource utilization in energy-constrained wireless sensor networks.