Abstract
In order to improve the invulnerability and adaptability in sensor networks, we propose a cellular automata (CA) based propagation control mechanism (CACM) to inhibit and monitor emergent-event contagion. The cellular evolving rules of CACM are figured in multi-dimension convolution operations and cell state transform, which can be utilized to model the complex behavior of sensor nodes by separating the intrinsic and extrinsic states for each network cell. Furthermore, inspired by burning pain for Wireworld based monitoring model, network entropy theory is introduced into layered states on CACM to construct particle-based information communication process by efficient distribution of event-related messages on network routers, thus an invulnerable and energy-efficient diffusion and monitoring being achieved. Experiment results prove that CACM can outperform traditional propagation models in adaptive invulnerability and self-recovery scalability on sensor networks for propagation control on malicious events.
This work was supported by the Science and Technology Commission of Shanghai Municipality (17511108604), the National Natural Science Foundation of China (61501187 and 61673178).
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Huang, R., Yang, H., Yang, H., Ma, L. (2020). A Generalized Cellular Automata Approach to Modelling Contagion and Monitoring for Emergent Events in Sensor Networks. In: Zhai, G., Zhou, J., Yang, H., An, P., Yang, X. (eds) Digital TV and Wireless Multimedia Communication. IFTC 2019. Communications in Computer and Information Science, vol 1181. Springer, Singapore. https://doi.org/10.1007/978-981-15-3341-9_26
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