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A CWMN Spectrum Allocation Based on Multi-strategy Fusion Glowworm Swarm Optimization Algorithm

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Wireless Internet (WICON 2016)

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Abstract

In cognitive wireless mesh networks, genetic algorithm based spectrum allocation has the problems of easily falling into local optimum, low accuracy and slow convergence. Aiming at the problems, glowworm swarm optimization is applied into spectrum allocation, and a multi-strategy fusion glowworm swarm optimization algorithm is proposed in this paper, in which step size and fluorescein volatilization factor are dynamically optimized and positions of the glowworms that has fallen into local optimum can be disturbed by Gauss mutation operator. Compared with genetic algorithm and basic glowworm swarm algorithm, the theoretical analysis and simulation results show that the proposed algorithm can avoid falling into local optimum, converge more quickly to the global optimal solution, and obtain higher system bandwidth reward.

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Acknowledgments

This paper was supported by the National Natural Science Foundation of China (Grant No. 61561017, Grant No. 61261024, and Grant No. 61363071), Doctoral Candidate Excellent Dissertation Cultivating Project of Hainan University, Postgraduate Practice and Innovation Project of Hainan University, and Major Science and Technology Project of Hainan Province under Grant No. ZDKJ2016015.

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Authors and Affiliations

  1. State Key Laboratory of Marine Resource Utilization in the South China Sea, Hainan University, No. 58, Renmin Avenue, Haikou, 570228, Hainan, People’s Republic of China

    Zhuhua Hu & Yong Bai

  2. College of Information Science and Technology, Hainan University, No. 58, Renmin Avenue, Haikou, 570228, Hainan, People’s Republic of China

    Zhuhua Hu, Yugui Han, Lu Cao, Yong Bai & Yaochi Zhao

Authors
  1. Zhuhua Hu
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  2. Yugui Han
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  3. Lu Cao
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  4. Yong Bai
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  5. Yaochi Zhao
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Corresponding author

Correspondence to Yong Bai .

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Editors and Affiliations

  1. Hainan University, Hainan, China

    Mengxing Huang

  2. Simula Research Laboratory, Fornebu, Norway

    Yan Zhang

  3. Northeast Forestry University, Harbin, Heilongjiang, China

    Weipeng Jing

  4. Guangdong University of Petrochemical Technology, Maoming Shi, China

    Amjad Mehmood

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Hu, Z., Han, Y., Cao, L., Bai, Y., Zhao, Y. (2018). A CWMN Spectrum Allocation Based on Multi-strategy Fusion Glowworm Swarm Optimization Algorithm. In: Huang, M., Zhang, Y., Jing, W., Mehmood, A. (eds) Wireless Internet. WICON 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 214. Springer, Cham. https://doi.org/10.1007/978-3-319-72998-5_12

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  • DOI: https://doi.org/10.1007/978-3-319-72998-5_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-72997-8

  • Online ISBN: 978-3-319-72998-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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