Epidemic spreading in wireless sensor networks with node sleep scheduling

TL;DR

This paper introduces a new epidemic spreading model for wireless sensor networks that incorporates node sleep scheduling, providing insights into how energy-efficient mechanisms influence virus propagation.

Contribution

It presents a novel epidemic model combining SIS dynamics with probabilistic sleep scheduling and derives spreading equations and thresholds using MMC.

Findings

Epidemic threshold is proportional to sleep and activation probabilities.

Numerical simulations validate the theoretical model.

Sleep scheduling impacts virus spread dynamics.

Abstract

Wireless Sensor Networks (WSNs) have become widely used in various fields like environmental monitoring, smart agriculture, and health care. However, their extensive usage also introduces significant vulnerabilities to cyber viruses. Addressing this security issue in WSNs is very challenging due to their inherent limitations in energy and bandwidth to implement real-time security measures. To tackle the virus issue, it is crucial to first understand how it spreads in WSNs. In this brief, 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. 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 of node sleeping and node activation probabilities.