Energy-Aware WiFi Network Selection via Forecasting Energy Consumption
Covering a wide area by a large number of WiFi networks is anticipated to become very popular with Internet-of-things (IoT) and initiatives such as smart cities. Such network configuration is normally realized through deploying a large number of access points (APs) with overlapped coverage. However,...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Polish Academy of Sciences
2020-06-01
|
| Series: | International Journal of Electronics and Telecommunications |
| Subjects: | |
| Online Access: | https://journals.pan.pl/Content/115210/PDF/46_2020.pdf |
| _version_ | 1811343596859686912 |
|---|---|
| author | Atef Abdrabou Mohamed Darwish Ahmed Dalao Mohammed AlKaabi Mahmoud Abutaqiya |
| author_facet | Atef Abdrabou Mohamed Darwish Ahmed Dalao Mohammed AlKaabi Mahmoud Abutaqiya |
| author_sort | Atef Abdrabou |
| collection | DOAJ |
| description | Covering a wide area by a large number of WiFi networks is anticipated to become very popular with Internet-of-things (IoT) and initiatives such as smart cities. Such network configuration is normally realized through deploying a large number of access points (APs) with overlapped coverage. However, the imbalanced traffic load distribution among different APs affects the energy consumption of a WiFi device if it is associated to a loaded AP. This research work aims at predicting the communication-related energy that shall be consumed by a WiFi device if it transferred some amount of data through a certain selected AP. In this paper, a forecast of the energy consumption is proposed to be obtained using an algorithm that is supported by a mathematical model. Consequently, the proposed algorithm can automatically select the best WiFi network (best AP) that the WiFi device can connect to in order to minimize energy consumption. The proposed algorithm is experimentally validated in a realistic lab setting. The observed performance indicates that the algorithm can provide an accurate forecast to the energy that shall be consumed by a WiFi transceiver in sending some amount of data via a specific AP. |
| first_indexed | 2024-04-13T19:32:46Z |
| format | Article |
| id | doaj.art-e43b7971294a479f89318b3bfb426763 |
| institution | Directory Open Access Journal |
| issn | 2081-8491 2300-1933 |
| language | English |
| last_indexed | 2024-04-13T19:32:46Z |
| publishDate | 2020-06-01 |
| publisher | Polish Academy of Sciences |
| record_format | Article |
| series | International Journal of Electronics and Telecommunications |
| spelling | doaj.art-e43b7971294a479f89318b3bfb4267632022-12-22T02:33:09ZengPolish Academy of SciencesInternational Journal of Electronics and Telecommunications2081-84912300-19332020-06-01vol. 66No 2339345https://doi.org/10.24425/ijet.2020.131883Energy-Aware WiFi Network Selection via Forecasting Energy ConsumptionAtef AbdrabouMohamed DarwishAhmed DalaoMohammed AlKaabiMahmoud AbutaqiyaCovering a wide area by a large number of WiFi networks is anticipated to become very popular with Internet-of-things (IoT) and initiatives such as smart cities. Such network configuration is normally realized through deploying a large number of access points (APs) with overlapped coverage. However, the imbalanced traffic load distribution among different APs affects the energy consumption of a WiFi device if it is associated to a loaded AP. This research work aims at predicting the communication-related energy that shall be consumed by a WiFi device if it transferred some amount of data through a certain selected AP. In this paper, a forecast of the energy consumption is proposed to be obtained using an algorithm that is supported by a mathematical model. Consequently, the proposed algorithm can automatically select the best WiFi network (best AP) that the WiFi device can connect to in order to minimize energy consumption. The proposed algorithm is experimentally validated in a realistic lab setting. The observed performance indicates that the algorithm can provide an accurate forecast to the energy that shall be consumed by a WiFi transceiver in sending some amount of data via a specific AP.https://journals.pan.pl/Content/115210/PDF/46_2020.pdfenergyconsumptionforecastwifiiot |
| spellingShingle | Atef Abdrabou Mohamed Darwish Ahmed Dalao Mohammed AlKaabi Mahmoud Abutaqiya Energy-Aware WiFi Network Selection via Forecasting Energy Consumption International Journal of Electronics and Telecommunications energy consumption forecast wifi iot |
| title | Energy-Aware WiFi Network Selection via Forecasting Energy Consumption |
| title_full | Energy-Aware WiFi Network Selection via Forecasting Energy Consumption |
| title_fullStr | Energy-Aware WiFi Network Selection via Forecasting Energy Consumption |
| title_full_unstemmed | Energy-Aware WiFi Network Selection via Forecasting Energy Consumption |
| title_short | Energy-Aware WiFi Network Selection via Forecasting Energy Consumption |
| title_sort | energy aware wifi network selection via forecasting energy consumption |
| topic | energy consumption forecast wifi iot |
| url | https://journals.pan.pl/Content/115210/PDF/46_2020.pdf |
| work_keys_str_mv | AT atefabdrabou energyawarewifinetworkselectionviaforecastingenergyconsumption AT mohameddarwish energyawarewifinetworkselectionviaforecastingenergyconsumption AT ahmeddalao energyawarewifinetworkselectionviaforecastingenergyconsumption AT mohammedalkaabi energyawarewifinetworkselectionviaforecastingenergyconsumption AT mahmoudabutaqiya energyawarewifinetworkselectionviaforecastingenergyconsumption |