ArticleEntropy (Basel, Switzerland)2021
Dynamics Analysis of a Wireless Rechargeable Sensor Network for Virus Mutation Spreading.
Article in Entropy (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Attention-Shared Multi-Agent Actor-Critic-Based Deep Reinforcement Learning Approach for Mobile Charging Dynamic Scheduling in Wireless Rechargeable Sensor Networks.Entropy (Basel, Switzerland) · 2022Article
- A Novel Epidemic Model Base on Pulse Charging in Wireless Rechargeable Sensor Networks.Entropy (Basel, Switzerland) · 2022Article
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Authors and funding
5 authors.
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Abstract
Virus spreading problems in wireless rechargeable sensor networks (WSNs) are becoming a hot topic, and the problem has been studied and discussed in recent years. Many epidemic spreading models have been introduced for revealing how a virus spreads and how a virus is suppressed. However, most of them assumed the sensors are not rechargeable sensors. In addition, most of existing works do not consider virus mutation problems. This paper proposes a novel epidemic model, including susceptible, infected, variant, low-energy and dead states, which considers the rechargeable sensors and the virus mutation factor. The stability of the proposed model is first analyzed by adopting the characteristic equation and constructing Lyapunov functions methods. Then, an optimal control problem is formulated to control the virus spread and decrease the cost of the networks by applying Pontryagin's maximum principle. Finally, all of the theoretical results are confirmed by numerical simulation.
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Registered trials
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