Modeling Optimal Location Distribution for Deployment of Flying Base Stations as On-Demand Connectivity Enablers in Real-World Scenarios
The amount of internet traffic generated during mass public events is significantly growing in a way that requires methods to increase the overall performance of the wireless network service. Recently, legacy methods in form of mobile cell sites, frequently called cells on wheels, were used. However...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-08-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/21/16/5580 |
| _version_ | 1797522122923311104 |
|---|---|
| author | Jiri Pokorny Pavel Seda Milos Seda Jiri Hosek |
| author_facet | Jiri Pokorny Pavel Seda Milos Seda Jiri Hosek |
| author_sort | Jiri Pokorny |
| collection | DOAJ |
| description | The amount of internet traffic generated during mass public events is significantly growing in a way that requires methods to increase the overall performance of the wireless network service. Recently, legacy methods in form of mobile cell sites, frequently called cells on wheels, were used. However, modern technologies are allowing the use of unmanned aerial vehicles (UAV) as a platform for network service extension instead of ground-based techniques. This results in the development of flying base stations (FBS) where the number of deployed FBSs depends on the demanded network capacity and specific user requirements. Large-scale events, such as outdoor music festivals or sporting competitions, requiring deployment of more than one FBS need a method to optimally distribute these aerial vehicles to achieve high capacity and minimize the cost. In this paper, we present a mathematical model for FBS deployment in large-scale scenarios. The model is based on a location set covering problem and the goal is to minimize the number of FBSs by finding their optimal locations. It is restricted by users’ throughput requirements and FBSs’ available throughput, also, all users that require connectivity must be served. Two meta-heuristic algorithms (cuckoo search and differential evolution) were implemented and verified on a real example of a music festival scenario. The results show that both algorithms are capable of finding a solution. The major difference is in the performance where differential evolution solves the problem six to eight times faster, thus it is more suitable for repetitive calculation. The obtained results can be used in commercial scenarios similar to the one used in this paper where providing sufficient connectivity is crucial for good user experience. The designed algorithms will serve for the network infrastructure design and for assessing the costs and feasibility of the use-case. |
| first_indexed | 2024-03-10T08:24:00Z |
| format | Article |
| id | doaj.art-fd09aea8208c44dc8de11959340092dd |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T08:24:00Z |
| publishDate | 2021-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-fd09aea8208c44dc8de11959340092dd2023-11-22T09:42:16ZengMDPI AGSensors1424-82202021-08-012116558010.3390/s21165580Modeling Optimal Location Distribution for Deployment of Flying Base Stations as On-Demand Connectivity Enablers in Real-World ScenariosJiri Pokorny0Pavel Seda1Milos Seda2Jiri Hosek3Department of Telecommunications, Faculty of Electrical Engineering and Communication, Brno University of Technology, Technicka 12, 616 00 Brno, Czech RepublicDepartment of Telecommunications, Faculty of Electrical Engineering and Communication, Brno University of Technology, Technicka 12, 616 00 Brno, Czech RepublicInstitute of Automation and Computer Science, Brno University of Technology, Technicka 2, 616 69 Brno, Czech RepublicDepartment of Telecommunications, Faculty of Electrical Engineering and Communication, Brno University of Technology, Technicka 12, 616 00 Brno, Czech RepublicThe amount of internet traffic generated during mass public events is significantly growing in a way that requires methods to increase the overall performance of the wireless network service. Recently, legacy methods in form of mobile cell sites, frequently called cells on wheels, were used. However, modern technologies are allowing the use of unmanned aerial vehicles (UAV) as a platform for network service extension instead of ground-based techniques. This results in the development of flying base stations (FBS) where the number of deployed FBSs depends on the demanded network capacity and specific user requirements. Large-scale events, such as outdoor music festivals or sporting competitions, requiring deployment of more than one FBS need a method to optimally distribute these aerial vehicles to achieve high capacity and minimize the cost. In this paper, we present a mathematical model for FBS deployment in large-scale scenarios. The model is based on a location set covering problem and the goal is to minimize the number of FBSs by finding their optimal locations. It is restricted by users’ throughput requirements and FBSs’ available throughput, also, all users that require connectivity must be served. Two meta-heuristic algorithms (cuckoo search and differential evolution) were implemented and verified on a real example of a music festival scenario. The results show that both algorithms are capable of finding a solution. The major difference is in the performance where differential evolution solves the problem six to eight times faster, thus it is more suitable for repetitive calculation. The obtained results can be used in commercial scenarios similar to the one used in this paper where providing sufficient connectivity is crucial for good user experience. The designed algorithms will serve for the network infrastructure design and for assessing the costs and feasibility of the use-case.https://www.mdpi.com/1424-8220/21/16/5580UAV base stationflying base stationFBSlocation optimizationnetwork coverage capacityon-demand |
| spellingShingle | Jiri Pokorny Pavel Seda Milos Seda Jiri Hosek Modeling Optimal Location Distribution for Deployment of Flying Base Stations as On-Demand Connectivity Enablers in Real-World Scenarios Sensors UAV base station flying base station FBS location optimization network coverage capacity on-demand |
| title | Modeling Optimal Location Distribution for Deployment of Flying Base Stations as On-Demand Connectivity Enablers in Real-World Scenarios |
| title_full | Modeling Optimal Location Distribution for Deployment of Flying Base Stations as On-Demand Connectivity Enablers in Real-World Scenarios |
| title_fullStr | Modeling Optimal Location Distribution for Deployment of Flying Base Stations as On-Demand Connectivity Enablers in Real-World Scenarios |
| title_full_unstemmed | Modeling Optimal Location Distribution for Deployment of Flying Base Stations as On-Demand Connectivity Enablers in Real-World Scenarios |
| title_short | Modeling Optimal Location Distribution for Deployment of Flying Base Stations as On-Demand Connectivity Enablers in Real-World Scenarios |
| title_sort | modeling optimal location distribution for deployment of flying base stations as on demand connectivity enablers in real world scenarios |
| topic | UAV base station flying base station FBS location optimization network coverage capacity on-demand |
| url | https://www.mdpi.com/1424-8220/21/16/5580 |
| work_keys_str_mv | AT jiripokorny modelingoptimallocationdistributionfordeploymentofflyingbasestationsasondemandconnectivityenablersinrealworldscenarios AT pavelseda modelingoptimallocationdistributionfordeploymentofflyingbasestationsasondemandconnectivityenablersinrealworldscenarios AT milosseda modelingoptimallocationdistributionfordeploymentofflyingbasestationsasondemandconnectivityenablersinrealworldscenarios AT jirihosek modelingoptimallocationdistributionfordeploymentofflyingbasestationsasondemandconnectivityenablersinrealworldscenarios |