WCL: Client Selection in Federated Learning with a Combination of Model Weight Divergence and Client Training Loss for Internet Traffic Classification

<div>FL framework overview; the figure shows the basic framework structure and process of FL. It can be seen from the figure that FL generally has 4 steps: (1) The server broadcasts the global model. (2) The client downloads the model and uses local data to train the model. (3) The client uploads the model parameters. (4) The server aggregates the client model parameters.</div>

Wireless Communications and Mobile Computing

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Figure 1: WCL: Client Selection in Federated Learning with a Combination of Model Weight Divergence and Client Training Loss for Internet Traffic Classification 

Figure 1 | WCL: Client Selection in Federated Learning with a Combination of Model Weight Divergence and Client Training Loss for Internet Traffic Classification 