Abstract
Due to the vulnerability of Internet of Things (IoT) to random failures, this study investigates resilience of an evolutionary computing model based on capacity efficiency and on-demand restoration to swiftly address node-link failures. Researches have been conducted on IoT network single failures, but multiple node-link failures have not received enough attention. The model was experimented on node-link failures at various locations on big networks. The proposed model could generate excellent alternate routes and the bandwidth needed for rapid rerouting of multimedia traffic. As multiple node-link failures increase, bandwidth usage also increases which slows down multimedia traffic routing. The proposed model outperforms common proactive and reactive models, in terms of throughput and running time. The survival solution paths show that the proposed model works well in avoiding data loss in transit in spite of multiple node-link failures. This new model is essential in this COVID-19 pandemic, which often requires emergency communications.
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Owoade, A.A., Osunmakinde, I.O. (2021). Resilient Rerouting in IoT Systems with Evolutionary Computing. In: Silhavy, R. (eds) Artificial Intelligence in Intelligent Systems. CSOC 2021. Lecture Notes in Networks and Systems, vol 229. Springer, Cham. https://doi.org/10.1007/978-3-030-77445-5_18
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DOI: https://doi.org/10.1007/978-3-030-77445-5_18
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