Abstract
As energy-harvesting wireless sensor networks (EHWSNs) are increasingly integrated with all walks of life, their security problems have gradually become hot issues. As an attack means, malicious programs often attack sensor nodes in critical locations in the networks to cause paralysis and information leakage of the networks, resulting in security risks. Based on the previous works and the introduction of solar charging, we proposed a novel model, namely, Susceptible-Infected-Low (energy)-Recovered-Dead (SILRD) with solar energy harvesters. Meanwhile, this paper takes Logistic Growth as the drop rate of sensor nodes and the infection rate of multitype malicious programs under nonlinear condition into consideration. Finally, an Λ-Susceptible-Infected-Low (energy)-Recovered-Dead (ΛSILRD) model is proposed. Based on the Pontryagin Maximum Principle, this paper proposes the optimal strategies based on the SILRD with solar energy harvesters and the ΛSILRD. The effectiveness of SILRD with solar energy harvesters was demonstrated by comparison with the general epidemic model. At the same time, by analyzing different charging strategies, we conclude that solar charging is highly efficient. Moreover, we further analyze the influence of controllable and uncontrollable input and various node degrees on ΛSILRD model.
Highlights
With the rapid development of wireless sensor networks (WSNs) in the past few years, the unique characteristics of WSNs have enabled them to play a key role in many fields, such as military strike, agricultural production, intelligent transportation, medical and health systems, and industrial fields
The limited energy vastly confines the lifetime of the networks. Renewable natural resources, such as wind, solar, and tidal energy, can be transferred to electricity by certain energy harvesters, which can greatly mitigate the impact of energy shortage on the lifetime of energy-harvesting wireless sensor networks (EHWSNs) which is equipped with energy harvesters on each sensor node
We will expand into three parts. e first part is to compare with the existing general epidemic models in turn. e second part is to analyze the impact of charging on the Susceptible-Infected-Low (energy)-Recovered-Dead (SILRD) model. e third part is to discuss the impact of controllable and uncontrollable system input and node degree on the Λ-Susceptible-InfectedLow (energy)-Recovered-Dead (ΛSILRD) model
Summary
With the rapid development of wireless sensor networks (WSNs) in the past few years, the unique characteristics of WSNs have enabled them to play a key role in many fields, such as military strike, agricultural production, intelligent transportation, medical and health systems, and industrial fields. At the same time, considering networks input and multitypes of malicious programs attacks with nonlinear infection rates, a novel model named Λ-Susceptible-Infected-Low (energy)Recovered-Dead (ΛSILRD) is proposed. Based on the ΛSILRD model, the optimal dynamic control strategies for EHWSNs and malicious programs under various node degrees are proposed by applying Pontryagin Maximum Principle. Sensor nodes in the infected state are transformed from susceptible, recovered, or low-energy sensor nodes by running malicious programs. The proportion of the number of sensor nodes in susceptible, infected, recovered, low-energy, and dead states is S(t), I(t), L(t), R(t), and D(t), respectively. Erefore, infected sensor nodes will consume the remaining electricity at a faster rate and transform to low-energy or dead state with probability PIL and PI D according to the attack power of malicious programs.
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