Target allocation of WSN based on Parallel Chaotic Elite Quantum-Inspired Evolutionary Algorithm

Zhou, J; Dutkiewicz, E; Liu, RP; Fang, G; Liu, Y

Target allocation of WSN based on Parallel Chaotic Elite Quantum-Inspired Evolutionary Algorithm

Zhou, J Dutkiewicz, E

Liu, RP

Fang, G Liu, Y

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Publication Type:: Conference Proceeding
Citation:: 2015 15th International Symposium on Communications and Information Technologies, ISCIT 2015, 2016, pp. 287 - 290
Issue Date:: 2016-04-22

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Field	Value	Language
dc.contributor.author	Zhou, J	en_US
dc.contributor.author	Dutkiewicz, E https://orcid.org/0000-0002-4268-9286	en_US
dc.contributor.author	Liu, RP https://orcid.org/0000-0001-7001-6305	en_US
dc.contributor.author	Fang, G	en_US
dc.contributor.author	Liu, Y	en_US
dc.date.issued	2016-04-22	en_US
dc.identifier.citation	2015 15th International Symposium on Communications and Information Technologies, ISCIT 2015, 2016, pp. 287 - 290	en_US
dc.identifier.isbn	9781467368209	en_US
dc.identifier.uri	http://hdl.handle.net/10453/102961
dc.description.abstract	© 2015 IEEE. The target allocation problem is one of the important challenges in WSNs as sensor nodes have limited sensing and communication capabilities. In the target allocation problem, a set of targets is selected for each sensor to improve the monitoring quality as well as the energy efficiency. However, the target allocation problem is a combinatorial optimization problem, and the computational complexity is too high to consider all combinations for practical implementation. In this paper, we propose a novel Parallel Chaotic Elite Quantum-Inspired Evolutionary Algorithm (PCEQEA) for target allocation problem in WSNs. The PCEQEA combines the advantages of elite genetic algorithm and quantum-inspired evolutionary algorithm. It achieves high parallel search performance and fast convergence to global optimum solution. Simulation results demonstrate that proposed PCEQEA improves WSN detection coverage by detecting more targets than other existing schemes.	en_US
dc.relation.ispartof	2015 15th International Symposium on Communications and Information Technologies, ISCIT 2015	en_US
dc.relation.isbasedon	10.1109/ISCIT.2015.7458363	en_US
dc.title	Target allocation of WSN based on Parallel Chaotic Elite Quantum-Inspired Evolutionary Algorithm	en_US
dc.type	Conference Proceeding
utslib.for	0806 Information Systems	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

© 2015 IEEE. The target allocation problem is one of the important challenges in WSNs as sensor nodes have limited sensing and communication capabilities. In the target allocation problem, a set of targets is selected for each sensor to improve the monitoring quality as well as the energy efficiency. However, the target allocation problem is a combinatorial optimization problem, and the computational complexity is too high to consider all combinations for practical implementation. In this paper, we propose a novel Parallel Chaotic Elite Quantum-Inspired Evolutionary Algorithm (PCEQEA) for target allocation problem in WSNs. The PCEQEA combines the advantages of elite genetic algorithm and quantum-inspired evolutionary algorithm. It achieves high parallel search performance and fast convergence to global optimum solution. Simulation results demonstrate that proposed PCEQEA improves WSN detection coverage by detecting more targets than other existing schemes.

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http://hdl.handle.net/10453/102961