Near optimal bounded route association for drone-enabled rechargeable WSNs
This paper considers the multi-drone wireless charging scheme in large scale wireless sensor networks, where sensors can be charged by the charging drone with wireless energy transfer. As existing studies rarely focus on the route association issue with limited energy capacity, we consider this fund...
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| Published in: | Computer networks (Amsterdam, Netherlands : 1999) Vol. 145; pp. 107 - 117 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
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Amsterdam
Elsevier B.V
09.11.2018
Elsevier Sequoia S.A |
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| ISSN: | 1389-1286, 1872-7069 |
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| Abstract | This paper considers the multi-drone wireless charging scheme in large scale wireless sensor networks, where sensors can be charged by the charging drone with wireless energy transfer. As existing studies rarely focus on the route association issue with limited energy capacity, we consider this fundamental issue and study how to optimize the route association to maximize the overall charging coverage utility, when charging routes and associated nodes should be jointly selected. We first formulate a bounded route association problem which is proven to be NP-hard. Then we cast it as maximizing a monotone submodular function subject to matroid constraints and devise an efficient and accessible algorithm with a 13α approximation ratio, where α is the bound of Fully Polynomial-Time Approximation Scheme (FPTAS) solving a knapsack problem. Extensive numerical evaluations and trace-driven evaluations have been carried out to validate our theoretical effect, and the results show that our algorithm has near-optimal performance covering at most 85.3% and 70.5% of the surrogate-optimal solution achieved by CPLEX toolbox, respectively. |
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| AbstractList | This paper considers the multi-drone wireless charging scheme in large scale wireless sensor networks, where sensors can be charged by the charging drone with wireless energy transfer. As existing studies rarely focus on the route association issue with limited energy capacity, we consider this fundamental issue and study how to optimize the route association to maximize the overall charging coverage utility, when charging routes and associated nodes should be jointly selected. We first formulate a bounded route association problem which is proven to be NP-hard. Then we cast it as maximizing a monotone submodular function subject to matroid constraints and devise an efficient and accessible algorithm with a ... approximation ratio, where α is the bound of Fully Polynomial-Time Approximation Scheme (FPTAS) solving a knapsack problem. Extensive numerical evaluations and trace-driven evaluations have been carried out to validate our theoretical effect, and the results show that our algorithm has near-optimal performance covering at most 85.3% and 70.5% of the surrogate-optimal solution achieved by CPLEX toolbox, respectively. (Proquest: ... denotes non-USASCII text omitted.) This paper considers the multi-drone wireless charging scheme in large scale wireless sensor networks, where sensors can be charged by the charging drone with wireless energy transfer. As existing studies rarely focus on the route association issue with limited energy capacity, we consider this fundamental issue and study how to optimize the route association to maximize the overall charging coverage utility, when charging routes and associated nodes should be jointly selected. We first formulate a bounded route association problem which is proven to be NP-hard. Then we cast it as maximizing a monotone submodular function subject to matroid constraints and devise an efficient and accessible algorithm with a 13α approximation ratio, where α is the bound of Fully Polynomial-Time Approximation Scheme (FPTAS) solving a knapsack problem. Extensive numerical evaluations and trace-driven evaluations have been carried out to validate our theoretical effect, and the results show that our algorithm has near-optimal performance covering at most 85.3% and 70.5% of the surrogate-optimal solution achieved by CPLEX toolbox, respectively. |
| Author | Wu, Tao Yang, Panlong Dai, Haipeng Li, Ping Rao, Xunpeng |
| Author_xml | – sequence: 1 givenname: Tao surname: Wu fullname: Wu, Tao email: terence.taowu@gmail.com organization: College of Communication Engineering, Army Engineering University, China – sequence: 2 givenname: Panlong surname: Yang fullname: Yang, Panlong email: panlongyang@gmail.com organization: College of Communication Engineering, Army Engineering University, China – sequence: 3 givenname: Haipeng orcidid: 0000-0001-8613-9051 surname: Dai fullname: Dai, Haipeng email: haipengdai@nju.edu.cn organization: Department of Computer Science and Technology, Nanjing University, China – sequence: 4 givenname: Ping surname: Li fullname: Li, Ping email: pingli0112@gmail.com organization: College of Communication Engineering, Army Engineering University, China – sequence: 5 givenname: Xunpeng surname: Rao fullname: Rao, Xunpeng email: raoxunpeng@gmail.com organization: College of Communication Engineering, Army Engineering University, China |
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| Cites_doi | 10.1109/ACCESS.2017.2665471 10.1109/TC.2014.2349521 10.1007/BFb0121195 10.1016/S0004-3702(98)00086-1 10.1504/IJSNET.2015.069862 10.1109/TMC.2016.2577585 10.1109/TVT.2015.2496971 10.1109/MWC.2013.6590061 10.1109/TMC.2010.193 10.1109/MASS.2016.029 10.1109/TNET.2017.2684159 10.1016/j.comcom.2014.03.001 10.1109/TMC.2014.2368557 10.1155/2015/286080 10.1109/TMC.2017.2748358 10.1145/1167935.1167936 10.1109/TMC.2006.109 10.1007/s10846-015-0175-5 |
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| Keywords | Wireless sensor networks Wireless charging Multiple knapsack problem Route association Drone system |
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| SubjectTerms | Algorithms Approximation Associations Drone system Energy Knapsack problem Mathematical analysis Multiple knapsack problem Optimization Polynomials Remote sensors Route association Sensors Wireless charging Wireless communication systems Wireless networks Wireless power transmission Wireless sensor networks |
| Title | Near optimal bounded route association for drone-enabled rechargeable WSNs |
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