Abstract
Deep learning is a promising way to get relevant information from IoT service sensor data embedded in complex situations. Due to its multifaceted structure, deep learning is better suited to the nature of computer drag. So, in the course of this article, we start by introducing deep IoT metrics into the computer environment. Because there is a limited amount of available bandwidth, we are designing a separate load-filling strategy to optimize the performance of deep IoT learning systems using computers (World Health Organization Epilepsy, http://www.who.int/mediacentre/factsheets/fs999/en/)
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Rajpoot, V., Patel, A., Manepalli, P.K., Saxena, A. (2021). Deep Learning and Edge Computing Solution for High-Performance Computing. In: Suresh, A., Paiva, S. (eds) Deep Learning and Edge Computing Solutions for High Performance Computing. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-60265-9_1
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DOI: https://doi.org/10.1007/978-3-030-60265-9_1
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