Federated Learning (FL) is a distributed machine learning technique, where each device contributes to the model by independently computing gradient based on its local training data. It has recently become hot research topic, as it promises several benefits related data privacy and scalability. However, implementing FL at network edge challenging due system heterogeneity resource constraints. In...