Epidemic spreading in wireless sensor networks with node sleep scheduling

Yanqing Wu, Cunlai Pu, Gongxuan Zhang, Lunbo Li, Yongxiang Xia and Chengyi Xia

Physica A: Statistical Mechanics and its Applications, 2023, vol. 629, issue C

Abstract: Understanding epidemic spreading processes in wireless sensor networks (WSNs) is crucial for the maintenance and protection of these networks. In this paper, we propose a novel epidemic spreading model for WSNs, integrating the susceptible–infected–susceptible (SIS) epidemic spreading model and node probabilistic sleep scheduling—a critical mechanism for optimizing energy efficiency. Using the microscopic Markov chain (MMC) method, we derive the spreading equations and epidemic threshold of our model, and further provide a lower bound for the epidemic threshold. We conduct numerical simulations to validate the theoretical results and investigate the impact of key factors on epidemic spreading in WSNs. Notably, we discover that the epidemic threshold is directly proportional to the ratio between node sleeping and node activation probabilities. This finding indicates that the scheduling of node sleeping can effectively suppress epidemic spreading in WSNs.

Keywords: Epidemic spreading; Epidemic threshold; Wireless sensor networks; Node sleep scheduling (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:629:y:2023:i:c:s0378437123007598

DOI: 10.1016/j.physa.2023.129204

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