@techreport{oai:ipsj.ixsq.nii.ac.jp:00216757,
 author = {Weichang, Zheng and Ziyu, Guo and Yongbing, Zhang and Weichang, Zheng and Ziyu, Guo and Yongbing, Zhang},
 issue = {1},
 month = {Feb},
 note = {With the rapid development and popularization of the Internet and communication technologies, the amount of network traffics has grown explosively. Network resources should be allocated to the applications depending on their requirements for quality of service (QoS). However, fast-growing new applications and protocols bring us difficulties and challenges to classify various traffics correctly. Machine learning-based techniques are expected to be a more time-saving and precise method for traffic classification depending on the quality of services of various applications. In this paper, we focus on the traffic QoS classification based on the deep learning technique with traditional traffic features along with a newly defined feature in this paper, that is, the time period of network traffic. Experimental results show that by considering the time period feature, the classification accuracy can be improved much better than before., With the rapid development and popularization of the Internet and communication technologies, the amount of network traffics has grown explosively. Network resources should be allocated to the applications depending on their requirements for quality of service (QoS). However, fast-growing new applications and protocols bring us difficulties and challenges to classify various traffics correctly. Machine learning-based techniques are expected to be a more time-saving and precise method for traffic classification depending on the quality of services of various applications. In this paper, we focus on the traffic QoS classification based on the deep learning technique with traditional traffic features along with a newly defined feature in this paper, that is, the time period of network traffic. Experimental results show that by considering the time period feature, the classification accuracy can be improved much better than before.},
 title = {Time-Aware Machine Learning-based Traffic QoS Classification},
 year = {2022}
}