Lifetime maximization of connected differentiated target coverage in energy harvesting directional sensor networks
Target surveillance applications of directional sensor networks are constantly emerging. The environmental energy harvesting technologies are promising solutions for alleviating the energy shortage in sensor networks. This work addresses the maximum lifetime target coverage problem in energy harvest...
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Published in | 2016 IEEE Online Conference on Green Communications (OnlineGreenComm) pp. 21 - 26 |
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Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.11.2016
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Abstract | Target surveillance applications of directional sensor networks are constantly emerging. The environmental energy harvesting technologies are promising solutions for alleviating the energy shortage in sensor networks. This work addresses the maximum lifetime target coverage problem in energy harvesting directional sensor networks. In this problem, the coverage quality requirements of all targets should be continuously satisfied and the network connectivity should be guaranteed. It is very challenging due to the limited sensing angle and the recharging ability of the sensors, and the different coverage quality requirements of the targets. We prove its NP-hardness and formulate it as a mixed integer nonlinear programming model. Two heuristics are proposed to solve it. Extensive simulations have been conducted to evaluate the performance of the proposed algorithms. |
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AbstractList | Target surveillance applications of directional sensor networks are constantly emerging. The environmental energy harvesting technologies are promising solutions for alleviating the energy shortage in sensor networks. This work addresses the maximum lifetime target coverage problem in energy harvesting directional sensor networks. In this problem, the coverage quality requirements of all targets should be continuously satisfied and the network connectivity should be guaranteed. It is very challenging due to the limited sensing angle and the recharging ability of the sensors, and the different coverage quality requirements of the targets. We prove its NP-hardness and formulate it as a mixed integer nonlinear programming model. Two heuristics are proposed to solve it. Extensive simulations have been conducted to evaluate the performance of the proposed algorithms. |
Author | Xiaojian Zhu |
Author_xml | – sequence: 1 surname: Xiaojian Zhu fullname: Xiaojian Zhu email: zhuxj5318@163.com organization: Sch. of Comput. Sci. & Eng., Changshu Inst. of Technol., Changshu, China |
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Snippet | Target surveillance applications of directional sensor networks are constantly emerging. The environmental energy harvesting technologies are promising... |
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SubjectTerms | Base stations Conferences Coverage quality directional sensor networks Energy harvesting Heuristic algorithms Learning automata network connectivity network lifetime Sensors Surveillance target coverage |
Title | Lifetime maximization of connected differentiated target coverage in energy harvesting directional sensor networks |
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