A Novel Epidemic Model Base on Pulse Charging in Wireless Rechargeable Sensor Networks

Area of Science:

• Computer Science
• Network Security
• Mathematical Modeling

Background:

• Wireless rechargeable sensor networks (WRSNs) face significant security challenges.
• Existing research often overlooks the potential of pulse charging strategies for WRSNs.
• Node energy utilization is a critical factor affecting WRSN performance and security.

Purpose of the Study:

• To propose a novel pulse infectious disease model (SIALS-P) for WRSNs that incorporates pulse charging.
• To address security issues in WRSNs by managing susceptible and infected nodes through energy replenishment.
• To analyze the stability and persistence of malware transmission within the proposed model.

Main Methods:

• Development of the SIALS-P model with susceptible, infected, anti-malware, and low-energy susceptible states.
• Application of Floquet theory for local stability analysis of the SIALS-P model.
• Utilizing a comparison system and theorem to analyze malware-free periodic solutions and transmission persistence.
• Analysis of optimal control strategies for the proposed model.
• Comparative simulations against non-charging and continuous charging models.

Main Results:

• The SIALS-P model effectively controls susceptible and infected nodes by converting low-energy nodes during periodic pulse charging.
• Stability analysis confirmed the behavior of the SIALS-P model under pulse charging.
• Simulation results demonstrate the superiority of the pulse charging model over non-charging and continuous charging models.
• Parameter effects on the basic reproduction number and sensitivity analysis were elucidated.

Conclusions:

• The proposed SIALS-P model offers a viable solution for enhancing WRSN security through pulse charging.
• Pulse charging is an effective strategy for improving node energy utilization and network stability.
• The study provides insights into malware dynamics and control in WRSNs, verified by optimal control theory.