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EiSIRS: a formal model to analyze the dynamics of worm propagation in wireless sensor networks

Author

Listed:
  • Xiaoming Wang

    (Shaanxi Normal University
    Georgia State University)

  • Qiaoliang Li

    (Georgia State University
    Hunan University)

  • Yingshu Li

    (Georgia State University)

Abstract

Based on the epidemic theory, this paper proposes a novel model for analyzing the dynamics of worm propagation in Wireless Sensor Networks (WSNs). The proposed model supports the sleep and work interleaving schedule policy for sensor nodes, and it can also describe the process of multi-worm propagation in WSNs. In addition, a necessary condition for worms to spread in WSNs is derived, which may be useful in designing a secure WSN. Simulation results show that the process of worm propagation in WSNs is sensitive to the energy consumption of nodes and the sleep and work interleaving schedule policy for nodes. Therefore, this paper provides new insights for the dynamics of worm propagation in WSNs.

Suggested Citation

  • Xiaoming Wang & Qiaoliang Li & Yingshu Li, 2010. "EiSIRS: a formal model to analyze the dynamics of worm propagation in wireless sensor networks," Journal of Combinatorial Optimization, Springer, vol. 20(1), pages 47-62, July.
    • Handle: RePEc:spr:jcomop:v:20:y:2010:i:1:d:10.1007_s10878-008-9190-9
    DOI: 10.1007/s10878-008-9190-9
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    Citations

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    Cited by:

    1. Jing Gao & Jianzhong Li & Yingshu Li, 2016. "Approximate event detection over multi-modal sensing data," Journal of Combinatorial Optimization, Springer, vol. 32(4), pages 1002-1016, November.
    2. Wu, Yanqing & Pu, Cunlai & Zhang, Gongxuan & Li, Lunbo & Xia, Yongxiang & Xia, Chengyi, 2023. "Epidemic spreading in wireless sensor networks with node sleep scheduling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 629(C).
    3. Wen Jiang & Zeyu Ma & Xinyang Deng, 2019. "An attack-defense game based reliability analysis approach for wireless sensor networks," International Journal of Distributed Sensor Networks, , vol. 15(4), pages 15501477198, April.

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