Energy Efficient Duty Cycle Design based on Quantum Immune Clonal Evolutionary Algorithm in Body Area Networks
Duty cycle design is an important topic in body area networks. As small sensors are equipped with the limited power source, the extension of network lifetime is generally achieved by reducing the network energy consumption, for instance through duty cycle schemes. However, the duty cycle design is a...
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European Alliance for Innovation (EAI)
2016-12-01
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Online Access: | http://eudl.eu/doi/10.4108/eai.28-9-2015.2261427 |
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doaj-f0bf8003174945818a5a87e9c7b7a9122020-11-25T02:11:09ZengEuropean Alliance for Innovation (EAI)EAI Endorsed Transactions on Energy Web2032-944X2016-12-01391410.4108/eai.28-9-2015.2261427Energy Efficient Duty Cycle Design based on Quantum Immune Clonal Evolutionary Algorithm in Body Area NetworksJie Zhou0Eryk Dutkiewicz1Ren Ping Liu2Gengfa Fang3Yuanan Liu4Macquarie UniversityMacquarie UniversityCSIRO; ren.liu@csiro.auMacquarie UniversityBeijing University of Posts and TelecommunicationsDuty cycle design is an important topic in body area networks. As small sensors are equipped with the limited power source, the extension of network lifetime is generally achieved by reducing the network energy consumption, for instance through duty cycle schemes. However, the duty cycle design is a highly complex NP-hard problem and its computational complexity is too high with exhaustive search algorithm for practical implementation. In order to extend the network lifetime, we proposed a novel quantum immune clonal evolutionary algorithm (QICEA) for duty cycle design while maintaining full coverage in the monitoring area. The QICEA is tested, and a performance comparison is made with simulated annealing (SA) and genetic algorithm (GA). Simulation results show that compared to the SA and the GA, the proposed QICEA can extending the lifetime of body area networks and enhancing the energy efficiency effectively.http://eudl.eu/doi/10.4108/eai.28-9-2015.2261427wireless sensor networksduty cycle designevolutionary algorithm |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jie Zhou Eryk Dutkiewicz Ren Ping Liu Gengfa Fang Yuanan Liu |
spellingShingle |
Jie Zhou Eryk Dutkiewicz Ren Ping Liu Gengfa Fang Yuanan Liu Energy Efficient Duty Cycle Design based on Quantum Immune Clonal Evolutionary Algorithm in Body Area Networks EAI Endorsed Transactions on Energy Web wireless sensor networks duty cycle design evolutionary algorithm |
author_facet |
Jie Zhou Eryk Dutkiewicz Ren Ping Liu Gengfa Fang Yuanan Liu |
author_sort |
Jie Zhou |
title |
Energy Efficient Duty Cycle Design based on Quantum Immune Clonal Evolutionary Algorithm in Body Area Networks |
title_short |
Energy Efficient Duty Cycle Design based on Quantum Immune Clonal Evolutionary Algorithm in Body Area Networks |
title_full |
Energy Efficient Duty Cycle Design based on Quantum Immune Clonal Evolutionary Algorithm in Body Area Networks |
title_fullStr |
Energy Efficient Duty Cycle Design based on Quantum Immune Clonal Evolutionary Algorithm in Body Area Networks |
title_full_unstemmed |
Energy Efficient Duty Cycle Design based on Quantum Immune Clonal Evolutionary Algorithm in Body Area Networks |
title_sort |
energy efficient duty cycle design based on quantum immune clonal evolutionary algorithm in body area networks |
publisher |
European Alliance for Innovation (EAI) |
series |
EAI Endorsed Transactions on Energy Web |
issn |
2032-944X |
publishDate |
2016-12-01 |
description |
Duty cycle design is an important topic in body area networks. As small sensors are equipped with the limited power source, the extension of network lifetime is generally achieved by reducing the network energy consumption, for instance through duty cycle schemes. However, the duty cycle design is a highly complex NP-hard problem and its computational complexity is too high with exhaustive search algorithm for practical implementation. In order to extend the network lifetime, we proposed a novel quantum immune clonal evolutionary algorithm (QICEA) for duty cycle design while maintaining full coverage in the monitoring area. The QICEA is tested, and a performance comparison is made with simulated annealing (SA) and genetic algorithm (GA). Simulation results show that compared to the SA and the GA, the proposed QICEA can extending the lifetime of body area networks and enhancing the energy efficiency effectively. |
topic |
wireless sensor networks duty cycle design evolutionary algorithm |
url |
http://eudl.eu/doi/10.4108/eai.28-9-2015.2261427 |
work_keys_str_mv |
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