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Maximum Power Transfer01:16

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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.
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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Energy Versus Throughput Optimisation for Machine-to-Machine Communication.

Emma Fitzgerald1,2, Michał Pióro2, Artur Tomaszewski2

  • 1Department of Electrical and Information Technology, Lund University, 221 00 Lund, Sweden.

Sensors (Basel, Switzerland)
|July 30, 2020
PubMed
Summary
This summary is machine-generated.

This study optimizes wireless mesh networks for machine-to-machine communication, balancing energy use and throughput. The novel model achieved simultaneous maximum throughput and minimum energy consumption in most tested scenarios.

Keywords:
IoTinteger programmingmachine-to-machine communicationmulticasttransmission schedulingwireless sensor networks

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Network Optimization

Background:

  • Machine-to-machine (M2M) communication relies on wireless mesh networks.
  • Balancing energy efficiency and data throughput is crucial for M2M networks.

Purpose of the Study:

  • To develop a novel optimization model for wireless mesh networks in M2M communication.
  • To investigate the trade-off between energy consumption and packet throughput.

Main Methods:

  • A novel mixed-integer programming formulation was developed.
  • A price-and-branch solution algorithm based on column generation was employed.
  • Numerical studies were conducted on network examples ranging from 10 to 40 nodes.

Main Results:

  • The optimization model successfully maximized throughput while minimizing energy usage in most cases.
  • When simultaneous optimization was not possible, the trade-off costs were minimal.
  • Solution times were on the order of seconds, demonstrating practical feasibility.

Conclusions:

  • The proposed optimization model effectively addresses the energy-throughput trade-off in wireless M2M networks.
  • The method is computationally efficient and suitable for practical implementation.
  • Simultaneous achievement of high throughput and low energy usage is often attainable.