Huan Zhang's research while affiliated with Hunan Normal University and other places
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Publications (2)
As network data keeps getting bigger, deep learning is coming to play a key role in network design and management. Meanwhile, accurate network traffic prediction is of critical importance for network management that is implemented to improve the quality of service (QoS) for users. However, the performance of existing network traffic prediction meth...
Aiming at the problem of network congestion and unbalanced load caused by a large amount of data capacity carried in elephant flow in the data center network, an elephant flow detection method based on SDN is proposed. This method adopts the autodetect upload (ADU) mechanism. ADU is divided into two parts: ADU-Client and ADU-Server, in which ADU-Cl...
Citations
... In the field of traffic prediction based on machine learning, Zhang et al. [19] introduced a model based on long short-term memory (LSTM) for network traffic predicting (LNTP) and a sliding window gradient descent (SWGD) algorithm for optimizing the weights of the neural network involved, specifically designed for an end-to-end online prediction model of network traffic. Nipun Ramakrishnan et al. [20] proposed several recurrent neural network (RNN) structures, including the standard RNN, LSTM network, and gated regression unit (GRU), to address the network traffic prediction problem. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/576002302906368-1514341058230_Q64/Lianming-Zhang.jpg)
... The authors described a framework to assist QoS equipping for reserving the resource demands of various kinds of data flows in reference [6]. It is feasible that there would not be sufficient accessible routes to redirect QoS flows, which results in deficient QoS flow transfer performance in complicated networks [7]. However, providing a high QoS level is difficult because of the many restrictions applied in the legacy networks. ...
Reference: Date of publication
