LCSA-Fed: A low cost semi-asynchronous federated learning based on lag tolerance for services QoS prediction
Lingru Cai,
Yuelong Liu,
Jianlong Xu
et al.
Abstract:As a distributed training method, federated learning (FL) has been widely used in the field of quality-of-service (QoS) prediction. However, existing FL-based QoS prediction methods ignore the unreliability of end devices, which will lead to wasted training resources and high communication costs. Considering that the instability of end devices in real training environments, we propose a low cost semi-asynchronous federated learning method (LCSA-Fed) based on lag tolerance to overcome the lower convergence rate… Show more
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