activity
20202022
most citedEsDNN: Deep Neural Network based Multivariate Workload Prediction Approach in Cloud Environment

133 citations · 136 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CR20221 cited

Joint Semantic Transfer Network for IoT Intrusion Detection

Jiashu Wu, Yang Wang, Binhui Xie +4

In this paper, we propose a Joint Semantic Transfer Network (JSTN) towards effective intrusion detection for large-scale scarcely labelled IoT domain. As a multi-source heterogeneo…

cs.DC2022133 cited

EsDNN: Deep Neural Network based Multivariate Workload Prediction Approach in Cloud Environment

Minxian Xu, Chenghao Song, Huaming Wu +3

Cloud computing has been regarded as a successful paradigm for IT industry by providing benefits for both service providers and customers. In spite of the advantages, cloud computi…

cs.LG20211 cited

Incorporating Reachability Knowledge into a Multi-Spatial Graph Convolution Based Seq2Seq Model for Traffic Forecasting

Jiexia Ye, Furong Zheng, Juanjuan Zhao +2

Accurate traffic state prediction is the foundation of transportation control and guidance. It is very challenging due to the complex spatiotemporal dependencies in traffic data. E…

cs.DC20211 cited

PDMA: Probabilistic Service Migration Approach for Delay-aware and Mobility-aware Mobile Edge Computing

Minxian Xu, Qiheng Zhou, Huaming Wu +3

As a key technology in the 5G era, Mobile Edge Computing (MEC) has developed rapidly in recent years. MEC aims to reduce the service delay of mobile users, while alleviating the pr…

eess.SP2020

How to Build a Graph-Based Deep Learning Architecture in Traffic Domain: A Survey

Jiexia Ye, Juanjuan Zhao, Kejiang Ye +1

In recent years, various deep learning architectures have been proposed to solve complex challenges (e.g. spatial dependency, temporal dependency) in traffic domain, which have ach…