Generalizable and Interpretable Deep Learning for Network Congestion Prediction
2021 IEEE 29th International Conference on Network Protocols (ICNP)(2021)
摘要
While recent years have witnessed a steady trend of applying Deep Learning (DL) to networking systems, most of the underlying Deep Neural Networks (DNNs) suffer two major limitations. First, they fail to generalize to topologies unseen during training. This lack of generalizability hampers the ability of the DNNs to make good decisions every time the topology of the networking system changes. Seco...
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关键词
Deep learning,Training,Protocols,Network topology,Time series analysis,Predictive models,Market research
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