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401397

Comparative Analysis of Resource Allocation Strategies in LoRa Networks: Optimizing Performance and Power Efficiency

Article

Last updated: 20 Jan 2025

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Tags

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Abstract

Internet-of-things (IoT) systems are expected to be integral to every aspect of human life. The number of IoT applications is exponentially growing, especially the low-power wide-area network (LPWAN). LPWAN is an emerging IoT networking paradigm with three main characteristics: low-cost, large-scale deployment, and high energy efficiency. IoT systems are becoming more and more important in a variety of areas, and LPWAN are essential because of their affordability, scalability, and energy efficiency (EE). One of the most popular LPWAN technologies, LoRaWAN, has performance issues with resource allocation (RA). This article investigates the architecture of the LoRaWAN network, emphasizing its primary resources and their characteristics. We classify current RA approaches, talk about important obstacles, and investigate future perspectives for LoRaWAN RA research. We also report a case study that improves resource distribution in LoRa networks by applying Spreading Factor Optimization (SFO) and the Hungarian algorithm. Our results demonstrate that, in comparison to conventional methods, the suggested SFO and Hungarian-based RA algorithms efficiently lower power consumption and enhance EE.

DOI

10.21608/erjsh.2024.314996.1342

Keywords

LoRa, LoRaWAN, resource allocation, Hungarian Algorithm, Spreading Factor Optimization algorithm

Authors

First Name

Manar

Last Name

Salah

MiddleName

M.

Affiliation

Department of Electrical Engineering, Faculty of Engineering at Shoubra, Benha University, Cairo, Egypt.

Email

manar.msalah90@gmail.com

City

cairo

Orcid

-

First Name

Basem

Last Name

Mamdoh

MiddleName

-

Affiliation

Electronics and Communication Engineering Department, Kuwait College of Science and Technology, Doha District, Block 4, 93004 Kuwait, Department of Electrical Engineering, Faculty of Engineering at Shoubra, Benha University, Cairo, Egypt.

Email

basem.mamdoh@feng.bu.edu.eg

City

Doha

Orcid

-

First Name

Reham

Last Name

Saad

MiddleName

S.

Affiliation

Department of Electrical Engineering, Faculty of Engineering at Shoubra, Benha University, Cairo, Egypt.

Email

reham.naseer@feng.bu.edu.eg

City

cairo

Orcid

-

First Name

Rokaia

Last Name

Emam

MiddleName

Mounir

Affiliation

Higher Institute of Engineering and Technology, Kafr El-Shaikh 33514 , Egypt., Department of Electrical Engineering, Faculty of Engineering at Shoubra, Benha University, Cairo, Egypt.

Email

rukaia.emam@feng.bu.edu.eg

City

cairo

Orcid

0000-0002-7111-9389

Volume

53

Article Issue

4

Related Issue

51476

Issue Date

2024-10-01

Receive Date

2024-08-31

Publish Date

2024-10-01

Page Start

248

Page End

255

Print ISSN

3009-6049

Online ISSN

3009-6022

Link

https://erjsh.journals.ekb.eg/article_401397.html

Detail API

http://journals.ekb.eg?_action=service&article_code=401397

Order

401,397

Type

Research articles

Type Code

2,276

Publication Type

Journal

Publication Title

Engineering Research Journal (Shoubra)

Publication Link

https://erjsh.journals.ekb.eg/

MainTitle

Comparative Analysis of Resource Allocation Strategies in LoRa Networks: Optimizing Performance and Power Efficiency

Details

Type

Article

Created At

20 Jan 2025