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A QoE-based dynamic energy-efficient network selection algorithm

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Abstract

For different network traffic and network state’s time-varying characteristics, this paper studies the highly energy-efficient network selection algorithm under dynamic change. Network selection algorithm has an important impact on network performance and users’ experience, while current network selection schemes depend on a prior. They cannot effectively select the appropriate network. Targeting users’ quality of experience (QoE) and networks’ energy consumption, this paper uses online dynamic learning property of Q-learning method, consider users’ QoE, networks’ energy consumption, and switch times together, and proposes a QoE based dynamic network selection algorithm. This algorithm can dynamically select the network, obtain the maximum users’ QoE and optimize networks’ energy consumption and switch times. Simulation results show that the proposed algorithm exhibits better performance.

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Acknowledgement

This work was supported by National Natural Science Foundation of China (No. 61571104), Sichuan Science and Technology Program (No. 2018JY0539), Key projects of the Sichuan Provincial Education Department (No. 18ZA0219), Fundamental Research Funds for the Central Universities (No. ZYGX2017KYQD170), and Innovation Funding (No. 2018510007000134). The authors wish to thank the reviewers for their helpful comments.

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Authors and Affiliations

  1. College of Information Security Engineering, Chengdu University of Information Technology, Chengdu, 610225, China

    Linbo He

  2. School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Dingde Jiang

  3. School of Computer Science and Engineering, Northeastern University, Shenyang, 110819, China

    Chao Wei

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  1. Linbo He
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  2. Dingde Jiang
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  3. Chao Wei
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Correspondence to Dingde Jiang.

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He, L., Jiang, D. & Wei, C. A QoE-based dynamic energy-efficient network selection algorithm. Wireless Netw 27, 3585–3595 (2021). https://doi.org/10.1007/s11276-019-02231-z

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