Hybrid Path Planning for Efficient Data Collection in UAV-Aided WSNs for Emergency Applications
In unmanned aerial vehicle (UAV)-aided wireless sensor networks (UWSNs), a UAV is employed as a mobile sink to gather data from sensor nodes. Incorporating UAV helps prolong the network lifetime and avoid the energy-hole problem faced by sensor networks. In emergency applications, timely data collec...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-04-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/21/8/2839 |
| _version_ | 1797537358792359936 |
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| author | Sabitri Poudel Sangman Moh |
| author_facet | Sabitri Poudel Sangman Moh |
| author_sort | Sabitri Poudel |
| collection | DOAJ |
| description | In unmanned aerial vehicle (UAV)-aided wireless sensor networks (UWSNs), a UAV is employed as a mobile sink to gather data from sensor nodes. Incorporating UAV helps prolong the network lifetime and avoid the energy-hole problem faced by sensor networks. In emergency applications, timely data collection from sensor nodes and transferal of the data to the base station (BS) is a prime requisite. The timely and safe path of UAV is one of the fundamental premises for effective UWSN operations. It is essential and challenging to identify a suitable path in an environment comprising various obstacles and to ensure that the path can efficiently reach the target point. This paper proposes a hybrid path planning (HPP) algorithm for efficient data collection by assuring the shortest collision-free path for UAV in emergency environments. In the proposed HPP scheme, the probabilistic roadmap (PRM) algorithm is used to design the shortest trajectory map and the optimized artificial bee colony (ABC) algorithm to improve different path constraints in a three-dimensional environment. Our simulation results show that the proposed HPP outperforms the PRM and conventional ABC schemes significantly in terms of flight time, energy consumption, convergence time, and flight path. |
| first_indexed | 2024-03-10T12:14:01Z |
| format | Article |
| id | doaj.art-fa1b4cd27e434589bf054c2fedcf8ad9 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T12:14:01Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-fa1b4cd27e434589bf054c2fedcf8ad92023-11-21T16:00:44ZengMDPI AGSensors1424-82202021-04-01218283910.3390/s21082839Hybrid Path Planning for Efficient Data Collection in UAV-Aided WSNs for Emergency ApplicationsSabitri Poudel0Sangman Moh1Department of Computer Engineering, Chosun University, 309 Pilmun-daero, Dong-gu, Gwangju 61452, KoreaDepartment of Computer Engineering, Chosun University, 309 Pilmun-daero, Dong-gu, Gwangju 61452, KoreaIn unmanned aerial vehicle (UAV)-aided wireless sensor networks (UWSNs), a UAV is employed as a mobile sink to gather data from sensor nodes. Incorporating UAV helps prolong the network lifetime and avoid the energy-hole problem faced by sensor networks. In emergency applications, timely data collection from sensor nodes and transferal of the data to the base station (BS) is a prime requisite. The timely and safe path of UAV is one of the fundamental premises for effective UWSN operations. It is essential and challenging to identify a suitable path in an environment comprising various obstacles and to ensure that the path can efficiently reach the target point. This paper proposes a hybrid path planning (HPP) algorithm for efficient data collection by assuring the shortest collision-free path for UAV in emergency environments. In the proposed HPP scheme, the probabilistic roadmap (PRM) algorithm is used to design the shortest trajectory map and the optimized artificial bee colony (ABC) algorithm to improve different path constraints in a three-dimensional environment. Our simulation results show that the proposed HPP outperforms the PRM and conventional ABC schemes significantly in terms of flight time, energy consumption, convergence time, and flight path.https://www.mdpi.com/1424-8220/21/8/2839wireless sensor networkdata gatheringunmanned aerial vehiclepath planningartificial bee colonycollision avoidance |
| spellingShingle | Sabitri Poudel Sangman Moh Hybrid Path Planning for Efficient Data Collection in UAV-Aided WSNs for Emergency Applications Sensors wireless sensor network data gathering unmanned aerial vehicle path planning artificial bee colony collision avoidance |
| title | Hybrid Path Planning for Efficient Data Collection in UAV-Aided WSNs for Emergency Applications |
| title_full | Hybrid Path Planning for Efficient Data Collection in UAV-Aided WSNs for Emergency Applications |
| title_fullStr | Hybrid Path Planning for Efficient Data Collection in UAV-Aided WSNs for Emergency Applications |
| title_full_unstemmed | Hybrid Path Planning for Efficient Data Collection in UAV-Aided WSNs for Emergency Applications |
| title_short | Hybrid Path Planning for Efficient Data Collection in UAV-Aided WSNs for Emergency Applications |
| title_sort | hybrid path planning for efficient data collection in uav aided wsns for emergency applications |
| topic | wireless sensor network data gathering unmanned aerial vehicle path planning artificial bee colony collision avoidance |
| url | https://www.mdpi.com/1424-8220/21/8/2839 |
| work_keys_str_mv | AT sabitripoudel hybridpathplanningforefficientdatacollectioninuavaidedwsnsforemergencyapplications AT sangmanmoh hybridpathplanningforefficientdatacollectioninuavaidedwsnsforemergencyapplications |