Design of Trusted Security Routing in Wireless Sensor Networks Based on Quantum Ant Colony Algorithm

Authors

  • Xiaobin Shu Department of Computer Science, Luohe Vocational College of Food, Luohe 462300，China
  • Caihong Liu Department of Computer Science, Luohe Vocational College of Food, Luohe 462300，China
  • Chunxia Jiao Department of Computer Science, Luohe Vocational College of Food, Luohe 462300，China
  • Qin Wang Department of Computer Science, Luohe Vocational College of Food, Luohe 462300，China
  • Hongfeng Yin Department of Computer Science, Beijing JiaoTong University Haibin College, Huanghua, 061199, China

DOI:

https://doi.org/10.3991/ijoe.v13i07.7273

Keywords:

wireless sensor network, quantum ant colony algorithm, safe and reliable, routing algorithm

Abstract


To design an effective secure routing of trusted nodes in wireless sensor networks, quantum ant colony algorithm is applied to the design of large-scale wireless sensor network routing. The trustworthy network is used as the pheromone distribution strategy.Then, the pheromone is encoded by the quantum bit. The pheromone is updated by the quantum revolving door, and the energy consumption prediction is carried out to select the path. Finally, the trusted security routing algorithm of the wireless sensor network based on the global energy balance is realized. The quantum ant colony algorithm is superior to the traditional ant colony algorithm in algorithm convergence speed and global optimization. It can balance the energy consumption of the network node and can effectively resist the attacks such as Wormholes.It is very promising to apply the quantum ant colony algorithm to the routing algorithm of large scale wireless sensor networks.

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Published

2017-07-21

How to Cite

Shu, X., Liu, C., Jiao, C., Wang, Q., & Yin, H. (2017). Design of Trusted Security Routing in Wireless Sensor Networks Based on Quantum Ant Colony Algorithm. International Journal of Online and Biomedical Engineering (iJOE), 13(07), pp. 4–13. https://doi.org/10.3991/ijoe.v13i07.7273

Issue

Vol. 13 No. 07 (2017)

Section

Papers

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