A Novel Epidemic Model for Wireless Rechargeable Sensor Network Security

doi:10.3390/s21010123

. 2020 Dec 27;21(1):123.

doi: 10.3390/s21010123.

A Novel Epidemic Model for Wireless Rechargeable Sensor Network Security

Guiyun Liu¹, Baihao Peng², Xiaojing Zhong¹

Affiliations

¹ School of Mechanical and Electric Engineering, Guangzhou University, Guangzhou 510006, China.
² School of Electronics and Communication Engineering, Guangzhou University, Guangzhou 510006, China.

PMID: 33375512
PMCID: PMC7795025
DOI: 10.3390/s21010123

A Novel Epidemic Model for Wireless Rechargeable Sensor Network Security

Guiyun Liu et al. Sensors (Basel). 2020.

. 2020 Dec 27;21(1):123.

doi: 10.3390/s21010123.

Authors

Guiyun Liu¹, Baihao Peng², Xiaojing Zhong¹

Affiliations

¹ School of Mechanical and Electric Engineering, Guangzhou University, Guangzhou 510006, China.
² School of Electronics and Communication Engineering, Guangzhou University, Guangzhou 510006, China.

PMID: 33375512
PMCID: PMC7795025
DOI: 10.3390/s21010123

Abstract

With the development of wireless rechargeable sensor networks (WRSNs ), security issues of WRSNs have attracted more attention from scholars around the world. In this paper, a novel epidemic model, SILS(Susceptible, Infected, Low-energy, Susceptible), considering the removal, charging and reinfection process of WRSNs is proposed. Subsequently, the local and global stabilities of disease-free and epidemic equilibrium points are analyzed and simulated after obtaining the basic reproductive number R0. Detailedly, the simulations further reveal the unique characteristics of SILS when it tends to being stable, and the relationship between the charging rate and R0. Furthermore, the attack-defense game between malware and WRSNs is constructed and the optimal strategies of both players are obtained. Consequently, in the case of R0<1 and R0>1, the validity of the optimal strategies is verified by comparing with the non-optimal control group in the evolution of sensor nodes and accumulated cost.

Keywords: cyber security; optimal control; stability analysis; wireless rechargeable sensor network.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

**Figure 1**
Flow diagram of the Susceptible, Infected, Low-energy, Susceptible (SILS) Model.

**Figure 2**
Evolution of sensor nodes when $R_{0} < 1$ . Different colors indicate that the curves start at different boundaries. So do Figure 3, Figure 4 and Figure 5.

**Figure 3**
Variation of S, I and LI nodes when $R_{0} < 1$ .

**Figure 4**
Evolution of sensor nodes when $R_{0} > 1$ .

**Figure 5**
Variation of S, I and LI nodes when $R_{0} > 1$ .

**Figure 7**
Evolution of sensor nodes under four different cases.

**Figure 9**
Variation of control variables.

See this image and copyright information in PMC

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References

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[1] Rashid B., Rehmani M.H. Applications of wireless sensor networks for urban areas: A survey. J. Netw. Comput. Appl. 2016;60 doi: 10.1016/j.jnca.2015.09.008. - DOI

[2] Rashid B., Rehmani M.H. Applications of wireless sensor networks for urban areas: A survey. J. Netw. Comput. Appl. 2016;60 doi: 10.1016/j.jnca.2015.09.008. - DOI

[3] Yetgin H., Cheung K.T.K., El-Hajjar M., Hanzo L. A Survey of Network Lifetime Maximization Techniques in Wireless Sensor Networks. IEEE Commun. Surv. Tutor. 2017;19:828–854. doi: 10.1109/COMST.2017.2650979. - DOI

[4] Yetgin H., Cheung K.T.K., El-Hajjar M., Hanzo L. A Survey of Network Lifetime Maximization Techniques in Wireless Sensor Networks. IEEE Commun. Surv. Tutor. 2017;19:828–854. doi: 10.1109/COMST.2017.2650979. - DOI

[5] Zhang F., Zhang J., Qian Y.J. A Survey on Wireless Power Transfer based Charging Scheduling Schemes in Wireless Rechargeable Sensor Networks; Proceedings of the ICCSSE 2018; Wuhan, China. 21–23 August 2018.

[6] Zhang F., Zhang J., Qian Y.J. A Survey on Wireless Power Transfer based Charging Scheduling Schemes in Wireless Rechargeable Sensor Networks; Proceedings of the ICCSSE 2018; Wuhan, China. 21–23 August 2018.

[7] Shu Y.C., Yousefi H., Cheng P., Chen J.M., Gu Y., He T., Shin K.G. Near-Optimal Velocity Control for Mobile Charging in Wireless Rechargeable Sensor Networks. IEEE. Trans. Mob. Comput. 2016;15:1699–1713. doi: 10.1109/TMC.2015.2473163. - DOI

[8] Shu Y.C., Yousefi H., Cheng P., Chen J.M., Gu Y., He T., Shin K.G. Near-Optimal Velocity Control for Mobile Charging in Wireless Rechargeable Sensor Networks. IEEE. Trans. Mob. Comput. 2016;15:1699–1713. doi: 10.1109/TMC.2015.2473163. - DOI

[9] Wu P.F., Xiao F., Sha C., Huang H.P., Sun L.J. Trajectory Optimization for UAVs’ Efficient Charging in Wireless Rechargeable Sensor Networks. IEEE Trans. Veh. Technol. 2020;69:4207–4220. doi: 10.1109/TVT.2020.2969220. - DOI

[10] Wu P.F., Xiao F., Sha C., Huang H.P., Sun L.J. Trajectory Optimization for UAVs’ Efficient Charging in Wireless Rechargeable Sensor Networks. IEEE Trans. Veh. Technol. 2020;69:4207–4220. doi: 10.1109/TVT.2020.2969220. - DOI

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A Novel Epidemic Model for Wireless Rechargeable Sensor Network Security

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A Novel Epidemic Model for Wireless Rechargeable Sensor Network Security

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Conflict of interest statement

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