Skip to main content
SpringerLink
Log in

A Dual SIS Epidemic Model for Virus Spread Analysis in Cluster-Based Wireless Sensor Networks

  • Conference paper
  • First Online:
Machine Learning and Intelligent Communications (MLICOM 2018)

Abstract

In this paper, we propose a dual SIS epidemic model to study the dynamics of virus spread for a cluster-based wireless sensor network (WSN). The dual SIS model consists of two groups of general sensor nodes (SNs) and cluster heads (CHs) and describes the dynamics of virus spread through the interactions among the SNs and CHs. We transfer the proposed model to a nonlinear system of differential equations and perform detailed analysis about equilibrium points and stability. We develop the system stability conditions (i.e., R0 and R1) and draw the conclusions for the proposed system. Under specific conditions, the epidemic (virus spread) in both groups will either die out with any number of initial infectives or remain endemic and the number of infectives in each group will approach a nonzero constant positive level. We provide numerical results to validate our analysis. The proposed model and analysis is applicable to different types of networks with multiple groups of users.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Tang, S., Li, W.: QoS supporting and optimal energy allocation for a cluster-based wireless sensor network. Comput. Commun. 29(13–14), 2569–2577 (2006)

    Article  Google Scholar 

  2. Younis, M., Youssef, M., Arisha, K.: Energy-aware routing in cluster based sensor networks. In: Proceedings of 10th IEEE/ACM Symposium on Modeling, Analysis and Simulation of Computer and Telecom Systems (MASCOTS 2002), Fort Worth, TX (2002)

    Google Scholar 

  3. Wang, T., et al.: Propagation modeling and defending of a mobile sensor worm in wireless sensor and actuator networks. Sensors 17(1), 139 (2017). https://doi.org/10.3390/s17010139

    Article  MathSciNet  Google Scholar 

  4. Tang, S., Mark, B.L.: Analysis of virus spread in wireless sensor networks: an epidemic model. In: 7th International Workshop on the Design of Reliable Communication Networks (DRCN 2009), Washington D.C., USA, 25–28 October 2009 (2009)

    Google Scholar 

  5. Tang, S., Myers, D., Yuan, J.: Modified SIS epidemic model for analysis of virus spread in wireless sensor networks. Int. J. Wirel. Mob. Comput. 6(2), 99–108 (2013)

    Article  Google Scholar 

  6. Mishra, B.K., Srivastava, S.K., Mishra, B.: A quarantine model on the spreading behavior of worms in wireless sensor network. Trans. IoT Cloud Comput. 2(1), 1–12 (2014)

    Article  Google Scholar 

  7. Ho, J.-W.: Hop-by-hop worm propagation with carryover epidemic model in mobile sensor networks. Computers 4(4), 283–292 (2015). https://doi.org/10.3390/computers4040283

    Article  Google Scholar 

  8. Khanh, N.H.: Dynamics of a worm propagation model with quarantine in wireless sensor networks. Appl. Math. Inf. Sci. 10(5), 1739–1746 (2016)

    Article  MathSciNet  Google Scholar 

  9. Upadhyay, R.K., Kumari, S.: Bifurcation analysis of an e-epidemic model in wireless sensor network. Int. J. Comput. Math. (2017). https://doi.org/10.1080/00207160.2017.1336550

    Article  MathSciNet  Google Scholar 

  10. Brannan, J.R., Boyce, W.E.: Differential Equations: An Introduction to Modern Methods and Applications, 3rd edn. Wiley, Hoboken (2015)

    MATH  Google Scholar 

  11. Sanchez, D.A.: Ordinary Differential Equations and Stability Theory: An Introduction. Dover Publications, New York (2012)

    Google Scholar 

Download references

Acknowledgments

This work was supported in part by the National Natural Science Foundation of China under Grant No. 61462020.

Author information

Authors and Affiliations

  1. Missouri Western State University, St. Joseph, MO, 64506, USA

    Shensheng Tang

  2. Guilin University of Electronic Technology, Guilin, 541004, China

    Chenghua Tang

Authors
  1. Shensheng Tang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chenghua Tang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shensheng Tang .

Editor information

Editors and Affiliations

  1. Zhejiang University of Technology, Hangzhou Shi, China

    Limin Meng

  2. Department of Networks, Simula Research Laboratory, Oslo, Norway

    Yan Zhang

Rights and permissions

Reprints and permissions

Copyright information

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

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Tang, S., Tang, C. (2018). A Dual SIS Epidemic Model for Virus Spread Analysis in Cluster-Based Wireless Sensor Networks. In: Meng, L., Zhang, Y. (eds) Machine Learning and Intelligent Communications. MLICOM 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 251. Springer, Cham. https://doi.org/10.1007/978-3-030-00557-3_65

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-00557-3_65

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00556-6

  • Online ISBN: 978-3-030-00557-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation