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Wireless Sensor Network Coverage Optimization based on Whale Group Algorithm
Computer Science and Information Systems, Tome 15 (2018) no. 3.

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For all of types of applications in wireless sensor networks (WSNs), coverage is a fundamental and hot topic research issue. To monitor the interest field and obtain the valid data, the paper proposes a wireless sensor network coverage optimization model based on improved whale algorithm. The mathematic model of node coverage in wireless sensor networks is developed to achieve full coverage for the interest area. For the model, the idea of reverse learning is introduced into the original whale swarm optimization algorithm to optimize the initial distribution of the population. This method enhances the node search capability and speeds up the global search. The experiment shows that this algorithm can effectively improve the coverage of nodes in wireless sensor networks and optimize the network performance.
Keywords: wireless sensor network, coverage optimization, whale swarm algorithm, reverse learning 
@article{CSIS_2018_15_3_a8,
     author = {Lei Wang and Weihua Wu and Junyan Qi and Zongpu Jia},
     title = {Wireless {Sensor} {Network} {Coverage} {Optimization} based on {Whale} {Group} {Algorithm}},
     journal = {Computer Science and Information Systems},
     publisher = {mathdoc},
     volume = {15},
     number = {3},
     year = {2018},
     url = {http://geodesic.mathdoc.fr/item/CSIS_2018_15_3_a8/}
}
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AU  - Lei Wang
AU  - Weihua Wu
AU  - Junyan Qi
AU  - Zongpu Jia
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JO  - Computer Science and Information Systems
PY  - 2018
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IS  - 3
PB  - mathdoc
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ID  - CSIS_2018_15_3_a8
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%I mathdoc
%U http://geodesic.mathdoc.fr/item/CSIS_2018_15_3_a8/
%F CSIS_2018_15_3_a8
Lei Wang; Weihua Wu; Junyan Qi; Zongpu Jia. Wireless Sensor Network Coverage Optimization based on Whale Group Algorithm. Computer Science and Information Systems, Tome 15 (2018) no. 3. http://geodesic.mathdoc.fr/item/CSIS_2018_15_3_a8/