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Impact of reduced scale free network on wireless sensor network

Author

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  • Keshri, Neha
  • Gupta, Anurag
  • Mishra, Bimal Kumar

Abstract

In heterogeneous wireless sensor network (WSN) each data-packet traverses through multiple hops over restricted communication range before it reaches the sink. The amount of energy required to transmit a data-packet is directly proportional to the number of hops. To balance the energy costs across the entire network and to enhance the robustness in order to improve the lifetime of WSN becomes a key issue of researchers. Due to high dimensionality of an epidemic model of WSN over a general scale free network, it is quite difficult to have close study of network dynamics. To overcome this complexity, we simplify a general scale free network by partitioning all of its motes into two classes: higher-degree motes and lower-degree motes, and equating the degrees of all higher-degree motes with lower-degree motes, yielding a reduced scale free network. We develop an epidemic model of WSN based on reduced scale free network. The existence of unique positive equilibrium is determined with some restrictions. Stability of the system is proved. Furthermore, simulation results show improvements made in this paper have made the entire network have a better robustness to the network failure and the balanced energy costs. This reduced model based on scale free network theory proves more applicable to the research of WSN.

Suggested Citation

  • Keshri, Neha & Gupta, Anurag & Mishra, Bimal Kumar, 2016. "Impact of reduced scale free network on wireless sensor network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 236-245.
  • Handle: RePEc:eee:phsmap:v:463:y:2016:i:c:p:236-245
    DOI: 10.1016/j.physa.2016.07.059
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    References listed on IDEAS

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    1. Yang, Lu-Xing & Yang, Xiaofan, 2014. "The spread of computer viruses over a reduced scale-free network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 396(C), pages 173-184.
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    Cited by:

    1. Zizhen Zhang & Soumen Kundu & Ruibin Wei, 2019. "A Delayed Epidemic Model for Propagation of Malicious Codes in Wireless Sensor Network," Mathematics, MDPI, vol. 7(5), pages 1-18, May.

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