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Related Experiment Video

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Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem

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LoRa-Based IoT Network Assessment in Rural and Urban Scenarios.

Aikaterini I Griva¹, Achilles D Boursianis¹, Shaohua Wan²

¹ELEDIA@AUTH, School of Physics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece.

Sensors (Basel, Switzerland)

|February 11, 2023

Summary

This summary is machine-generated.

Smart network performance using LoRa (Long Range) technology depends heavily on network parameters. Optimizing factors like transmission power and antenna gain significantly impacts energy consumption and data extraction rates in various environments.

Keywords:

Internet of Things (IoT)data extraction rate (DER)long-range network low-power wide-area network (LPWAN)network energy consumption (NEC)smart agriculture smart city

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Area of Science:

Computer Science
Electrical Engineering
Telecommunications

Background:

The Internet of Things (IoT) relies on smart networks for progress.
LoRa (Long Range) technology is key in IoT for its low-power, long-distance capabilities.

Purpose of the Study:

To model diverse environments and assess LoRa network performance.
To analyze the impact of various network parameters on key performance metrics.

Main Methods:

Simulations were conducted using OMNeT++ with the FLoRa framework.
Performance was evaluated across rural, urban, and parking area scenarios.

Main Results:

Path loss, deployment size, transmission power, spreading factor, node/gateway count, and antenna gain significantly affect LoRa network performance.
Key metrics include energy consumption and data extraction rate.

Conclusions:

Optimizing critical LoRa network parameters is essential for effective smart network deployment.
Simulation results highlight the influence of environmental factors and network configuration on overall efficiency.