Optimal Placement of Internet of Things Gateways in Modern Electric Vehicle Charging Communication Systems

This paper presents the use of the optimal placement and number of the Internet of Things (IoT) gateway method to support home Electric Vehicle (EV) charging scheduling within an IoT system. A research was conducted for two scenarios. In scenario 1, a single IoT gateway was placed, while in scenario 2, the optimal number of IoT gateways was placed. The evaluation method for both scenarios utilized random placement, Equally Distributed Placement (EDP), and Genetic Algorithm (GA) placement. The optimization result ensures that the Path Loss (PL) value in the communication system does not exceed the specified PL threshold. This research aims to minimize the IoT gateways while ensuring quality data transmission, specifically maintaining a data rate above 31.72 kbps and a throughput of 24 kbps. The results indicate that both the random placement and EDP require more than three IoT gateways. Meanwhile, the GA placement requires only three IoT gateways, making it a more cost-effective communication solution.

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Publication Details

Journal
Engineering Technology & Applied Science Research
Published
2025-04-03
DOI
https://doi.org/10.48084/etasr.9663
Citations
1
Primary Topic
Energy Harvesting in Wireless Networks
Type
article
Field-Weighted Citation Impact
0.73

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article

Optimal Placement of Internet of Things Gateways in Modern Electric Vehicle Charging Communication Systems

Heri Suryoatmojo, Syarifah Muthia Putri, Mochamad Ashari, Endroyono Endroyono
1 citations
Engineering Technology & Applied Science Research
Energy Harvesting in Wireless Networks
0.73
article

Optimal Placement of Internet of Things Gateways in Modern Electric Vehicle Charging Communication Systems

Heri Suryoatmojo, Syarifah Muthia Putri, Mochamad Ashari, Endroyono Endroyono
article en
1 citations

Abstract

This paper presents the use of the optimal placement and number of the Internet of Things (IoT) gateway method to support home Electric Vehicle (EV) charging scheduling within an IoT system. A research was conducted for two scenarios. In scenario 1, a single IoT gateway was placed, while in scenario 2, the optimal number of IoT gateways was placed. The evaluation method for both scenarios utilized random placement, Equally Distributed Placement (EDP), and Genetic Algorithm (GA) placement. The optimization result ensures that the Path Loss (PL) value in the communication system does not exceed the specified PL threshold. This research aims to minimize the IoT gateways while ensuring quality data transmission, specifically maintaining a data rate above 31.72 kbps and a throughput of 24 kbps. The results indicate that both the random placement and EDP require more than three IoT gateways. Meanwhile, the GA placement requires only three IoT gateways, making it a more cost-effective communication solution.

Engineering Technology & Applied Science ResearchVol. 15(2)
Sepuluh Nopember Institute of Technology (ID)
Lembaga Pengelola Dana Pendidikan
Openalex Percentile: Top 30%
Energy Harvesting in Wireless Networks
0.73
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