Enhancing Edge Computing Performance for IoT Applications Using Federated Learning Techniques
DOI:
https://doi.org/10.62951/ijcts.v1i1.57Keywords:
Edge computing, federated learning, IoT, data privacy, latency reductionAbstract
As Internet of Things (IoT) devices proliferate, edge computing has become essential for reducing latency and improving data privacy. This paper explores federated learning as a method to enhance the efficiency and security of edge computing systems. We implement and evaluate federated models in various IoT environments, demonstrating how federated learning can reduce data transfer and computation load while maintaining accuracy in data analysis.
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