Life Cycle and Intrusion Tolerance Optimization Topology Models for Wireless Sensor Networks

Authors

  • Jinhui Lei School of Information Engineering, Henan Institute of Science and Technology
  • Xiyan Tian School of Mechanical and Electrical Engineering, Henan Institute of Science and Technology
  • Zhixia Zhang School of Information Engineering, Henan Institute of Science and Technology

DOI:

https://doi.org/10.3991/ijoe.v14i05.8643

Keywords:

Wireless sensor networks, Network topology, Intrusion tolerance, Life cycle, En-ergy, Node failure

Abstract


Wireless sensor networks have such disadvantages as upper limit of node energy and poor intrusion tolerance, etc. In light of these disadvantages, by analyzing such key parameters as residual energy, load, node degree, this paper proposes a wireless sensor network (WSN) life-cycle model, which fully considers node energy consumption and load fault tolerance, and a scale-free intrusion tolerance and targeted attacks optimization topology model. Then it verifies their feasibility through simulation test. The results show that the WSN life cycle model takes into account the impacts of residual energy and load capacity on the life cycle and fault tolerance of the system and improves the connectivity probability of high energy consumption nodes and small load nodes, leading to more uniform energy consumption of the wireless sensor network. Through the load adjustment coefficient, the life cycle of the network model is significantly increased. The simulation results show that the fault tolerance and survival time of the proposed model are both improved to some extent compared with those of other models. The proposed scale-free intrusion tolerance and targeted attacks optimization topology model optimizes the power exponent of the network using the structure entropy, and the established scale-free topology structure can make the model more tolerant to intrusion. The simulation results show that the intrusion tolerance of the algorithm proposed in this paper is 2.5 times that of the traditional network model, and the average life cycle is also significantly increased compared to those of other models.

Author Biographies

Jinhui Lei, School of Information Engineering, Henan Institute of Science and Technology

Lei Jinhui received the B.S. degree in electronic information engineering and the M.S. degrees in communication and information system from Zhengzhou University in 2003 and 2011, respectively. He is currently a Lecturer with the School of Information Engineering, Henan Institute of Science and Technology, Xinxiang, China. His research interests include Internet of Things, embedded systems, and wireless sensor networks.

Xiyan Tian, School of Mechanical and Electrical Engineering, Henan Institute of Science and Technology

Tian Xiyan received the B.S. degree in applied electronic technology from Henan Normal University in 2002, and the M.S. degrees in communication and information system from Zhengzhou University in 2012. She is currently a Lecturer with the School of Mechanical and Electrical Engineering, Henan Institute of Science and Technology, Xinxiang, China. Her research interests include mobile communication network, wireless communication and electromagnetic compatibility, and cyber-physical systems.

Zhixia Zhang, School of Information Engineering, Henan Institute of Science and Technology

Zhang Zhixia, female, Lecturer. She graduated from Henan Institute of Science and Technology in September 2005, winning a bachelor’s degree in information engineering. In 2009 she graduated from Electronic Information College of Northwestern Polytechnical University, majoring in the signal and information processing, and received a master's degree. In July 2009 she came to Henan Institute of Science and Technology and worked in the College of Information Engineering. Her main research direction is the processing of intelligent signal and image.

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Published

2018-05-25

How to Cite

Lei, J., Tian, X., & Zhang, Z. (2018). Life Cycle and Intrusion Tolerance Optimization Topology Models for Wireless Sensor Networks. International Journal of Online and Biomedical Engineering (iJOE), 14(05), pp. 105–117. https://doi.org/10.3991/ijoe.v14i05.8643

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Section

Papers