A Novel Flash P2P Network Traffic Prediction Algorithm based on ELMD and Garch

Yimu Ji, Ye Wu, Dianchao Zhang, Yongge Yuan, Shangdong Liu, Roozbeh Zarei and Jing He
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Yimu Ji: School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu 210023, China†Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, Nanjing, Jiangsu 210023, China‡Institute of High-Performance Computing and Big Data, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu 210023, China§Nanjing Center of HPC China, Nanjing, Jiangsu 210023, China¶Jiangsu HPC and Intelligent Processing Engineer Research Center, Nanjing, Jiangsu 210023, China
Ye Wu: School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu 210023, China
Dianchao Zhang: School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu 210023, China
Yongge Yuan: School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu 210023, China
Shangdong Liu: School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu 210023, China‡Institute of High-Performance Computing and Big Data, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu 210023, China§Nanjing Center of HPC China, Nanjing, Jiangsu 210023, China¶Jiangsu HPC and Intelligent Processing Engineer Research Center, Nanjing, Jiangsu 210023, China
Roozbeh Zarei: #x2225;School of Information Technology, Deakin University, Burwood, VIC 3125, Australia**Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Zhejiang, Ningbo, China
Jing He: #x2020;†Institute of Information Technology, Nanjing University of Finance and Economics, Nanjing, Jiangsu 210023, China‡‡Software and Electrical Engineering, Swinburne University of Technology, Australia

International Journal of Information Technology & Decision Making (IJITDM), 2020, vol. 19, issue 01, 127-141

Abstract: To improve the quality of service and network performance for the Flash P2P video-on-demand, the prediction Flash P2P network traffic flow is beneficial for the control of the network video traffic. In this paper, a novel prediction algorithm to forecast the traffic rate of Flash P2P video is proposed. This algorithm is based on the combination of the ensemble local mean decomposition (ELMD) and the generalized autoregressive conditional heteroscedasticity (GARCH). The ELMD is used to decompose the original long-related flow into the summation of the short-related flow. Then, the GRACH is utilized to predict the short-related flow. The developed algorithm is tested in a university’s campus network. The predicted results show that our proposed method can further achieve higher accuracy than those obtained by existing algorithms, such as GARCH and Local Mean Decomposition and Generalized AutoRegressive Conditional Heteroskedasticity (LMD-GARCH) while keeping lower computational complexity.

Keywords: Self-similarity; ELMD; LMD; ARMA; GARCH; traffic prediction (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1142/S0219622019500469

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