k-means clustering algorithm. Finally, a prototype platform is developed to verify the proposed method experimentally, and compare the improved k-means clustering deployment method, k-means clustering deployment method, and random deployment method. The proposed method is superior to the other two methods regarding both network delay and computing resources deployment cost. The experimental results show that the proposed edge computing node deployment method can be easily applied to the intelligent manufacturing system; also, the effectiveness and efficiency of this method are verified.">

An Edge Computing Node Deployment Method Based on Improved k-Means Clustering Algorithm for Smart Manufacturing (original) (raw)

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