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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.
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.
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.

