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A hybrid service selection optimization algorithm in internet of things

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Abstract With the scale of Internet of Things (IoT) continues to increase, it brings big challenges for service selection in a large-scale IoT. For solving this problem, a service selection method based on the enhanced genetic algorithm is proposed in this paper. To decrease the scale of service selection, this paper uses the lexicographic optimization approach and quality of service (QoS) constraint relaxation technique to find the candidate service with height QoS. Then, the IoT service selection problem is transformed into a single-objective optimization problem adopting a simple weighting method, and the final composite service meeting the user's QoS needs are obtained from the candidate service. The simulation results show that the proposed algorithm can efficiently and quickly achieve a composite service satisfying user's QoS needs, and is more suitable for solving the service composite problem in large-scale IoT services.

Internet of thingsHybrid optimization algorithmService selectionQuality of service

Zhang Xiaofei、Geng Juncheng、Ma Jianwei、Liu Hao、Niu Shuangxia、Mao Wandeng

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Electric Power Research Institute of State Grid Henan Electric Power Company

2021

Eurasip Journal on Wireless Communications and Networking

Eurasip Journal on Wireless Communications and Networking

EISCI
ISSN:1687-1472
年,卷(期):2021.2021
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