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Related Concept Videos

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
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

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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...
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Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

653
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.
653
Network Function of a Circuit01:25

Network Function of a Circuit

948
Frequency response analysis in electrical circuits provides vital insights into a circuit's behavior as the frequency of the input signal changes. The transfer function, a mathematical tool, is instrumental in understanding this behavior. It defines the relationship between phasor output and input and comes in four types: voltage gain, current gain, transfer impedance, and transfer admittance. The critical components of the transfer function are the poles and zeros.
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Short-distance Transport of Resources02:12

Short-distance Transport of Resources

17.8K
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.
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Cluster Sampling Method01:20

Cluster Sampling Method

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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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Related Experiment Video

Updated: Feb 27, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

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A Smart and Balanced Energy-Efficient Multihop Clustering Algorithm (Smart-BEEM) for MIMO IoT Systems in Future

Lina Xu1, Gregory M P O'Hare2,3, Rem Collier4

  • 1School of Computer Science, University College Dublin, Belfield, Dublin 4, Ireland. lina.xu@ucd.ie.

Sensors (Basel, Switzerland)
|July 6, 2017
PubMed
Summary

This study introduces Smart-BEEM, a novel clustering algorithm for Internet of Things networks. It enhances energy efficiency and user experience by intelligently managing device communication and cluster heads, improving network longevity and coverage.

Keywords:
5GClusteringEnergy EfficiencyFuture NetworkIoTMIMOQoEWSN

Related Experiment Videos

Last Updated: Feb 27, 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

Area of Science:

  • Computer Science
  • Network Engineering
  • Wireless Communication

Background:

  • Wireless Sensor Networks (WSNs) face energy limitations, necessitating clustering for longevity and green computing.
  • Existing clustering methods often neglect network coverage when assessing network lifetime.
  • Internet of Things (IoT) technology introduces diverse communication abilities and user scenarios, demanding advanced clustering solutions.

Purpose of the Study:

  • To develop an advanced clustering solution for dynamic IoT systems with Multiple-In and Multiple-Out (MIMO) capabilities.
  • To enhance energy efficiency and Quality of User Experience (QoE) in cluster-based IoT networks.
  • To present Smart-BEEM, a user behavior and context-aware clustering algorithm.

Main Methods:

  • Building upon previous Balanced Energy-Efficiency (BEE) and BEEM algorithms.
  • Implementing a smart clustering algorithm (Smart-BEEM) for IoT networks.
  • Facilitating IoT devices to select optimal communication interfaces and cluster heads based on user behavior and context.

Main Results:

  • Smart-BEEM improves upon BEE and BEEM performance.
  • The algorithm enhances energy efficiency in IoT networks.
  • Coverage-sensitive network longevity is significantly improved.

Conclusions:

  • Smart-BEEM offers an advanced, context-aware clustering solution for dynamic IoT environments.
  • The algorithm effectively balances energy consumption and maintains network coverage.
  • Smart-BEEM is crucial for optimizing communication and user experience in diverse IoT applications.