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 in2016 IEEE Online Conference on Green Communications (OnlineGreenComm) pp. 21 - 26
Main Author Xiaojian Zhu
Format Conference Proceeding
LanguageEnglish
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.
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
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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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StartPage 21
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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