Joint Message-Passing and Convex Optimization Framework for Energy-Efficient Surveillance UAV Scheduling
In modern surveillance systems, the use of unmanned aerial vehicles (UAVs) has been actively discussed in order to extend target monitoring areas, even for an extreme circumstances. This paper proposes an energy-efficient UAV-based surveillance system that operates from two different sequential meth...
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doaj-711403921c44425baf06776444542a162020-11-25T02:30:43ZengMDPI AGElectronics2079-92922020-09-0191475147510.3390/electronics9091475Joint Message-Passing and Convex Optimization Framework for Energy-Efficient Surveillance UAV SchedulingSoyi Jung0Joongheon Kim1Jae-Hyun Kim2Department of Electrical and Computer Engineering, Ajou University, Suwon 16499, KoreaSchool of Electrical Engineering, Korea University, Seoul 02841, KoreaDepartment of Electrical and Computer Engineering, Ajou University, Suwon 16499, KoreaIn modern surveillance systems, the use of unmanned aerial vehicles (UAVs) has been actively discussed in order to extend target monitoring areas, even for an extreme circumstances. This paper proposes an energy-efficient UAV-based surveillance system that operates from two different sequential methods. First, the proposed algorithm pursues energy-efficient operations by deactivating selected surveillance cameras on the UAVs located in overlapping areas. For this objective, a message-passing based algorithm is used because the overlapping situations can be formulated using a max-weight independent set. Next, the unscheduled UAVs based on the message-passing fly to the charging towers to be charged. This algorithm computes the optimal matching between the UAVs and charging towers and the amount of energy allocation for the scheduled UAV-tower pairs. This joint optimization is initially formulated as non-convex, and it is then reformulated to be convex, which can guarantee optimal solutions. The proposed framework achieves the desired performance, as presented in the performance evaluation.https://www.mdpi.com/2079-9292/9/9/1475UAVssurveillanceenergy efficiencycharging schedulingoptimization |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Soyi Jung Joongheon Kim Jae-Hyun Kim |
spellingShingle |
Soyi Jung Joongheon Kim Jae-Hyun Kim Joint Message-Passing and Convex Optimization Framework for Energy-Efficient Surveillance UAV Scheduling Electronics UAVs surveillance energy efficiency charging scheduling optimization |
author_facet |
Soyi Jung Joongheon Kim Jae-Hyun Kim |
author_sort |
Soyi Jung |
title |
Joint Message-Passing and Convex Optimization Framework for Energy-Efficient Surveillance UAV Scheduling |
title_short |
Joint Message-Passing and Convex Optimization Framework for Energy-Efficient Surveillance UAV Scheduling |
title_full |
Joint Message-Passing and Convex Optimization Framework for Energy-Efficient Surveillance UAV Scheduling |
title_fullStr |
Joint Message-Passing and Convex Optimization Framework for Energy-Efficient Surveillance UAV Scheduling |
title_full_unstemmed |
Joint Message-Passing and Convex Optimization Framework for Energy-Efficient Surveillance UAV Scheduling |
title_sort |
joint message-passing and convex optimization framework for energy-efficient surveillance uav scheduling |
publisher |
MDPI AG |
series |
Electronics |
issn |
2079-9292 |
publishDate |
2020-09-01 |
description |
In modern surveillance systems, the use of unmanned aerial vehicles (UAVs) has been actively discussed in order to extend target monitoring areas, even for an extreme circumstances. This paper proposes an energy-efficient UAV-based surveillance system that operates from two different sequential methods. First, the proposed algorithm pursues energy-efficient operations by deactivating selected surveillance cameras on the UAVs located in overlapping areas. For this objective, a message-passing based algorithm is used because the overlapping situations can be formulated using a max-weight independent set. Next, the unscheduled UAVs based on the message-passing fly to the charging towers to be charged. This algorithm computes the optimal matching between the UAVs and charging towers and the amount of energy allocation for the scheduled UAV-tower pairs. This joint optimization is initially formulated as non-convex, and it is then reformulated to be convex, which can guarantee optimal solutions. The proposed framework achieves the desired performance, as presented in the performance evaluation. |
topic |
UAVs surveillance energy efficiency charging scheduling optimization |
url |
https://www.mdpi.com/2079-9292/9/9/1475 |
work_keys_str_mv |
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