Simulation Tools and Techniques. 11th International Conference, SIMUtools 2019, Chengdu, China, July 8–10, 2019, Proceedings

Research Article

A SDN-Based Network Traffic Estimating Algorithm in Power Telecommunication Network

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  • @INPROCEEDINGS{10.1007/978-3-030-32216-8_9,
        author={Renxiang Huang and Huibin Jia and Xing Huang},
        title={A SDN-Based Network Traffic Estimating Algorithm in Power Telecommunication Network},
        proceedings={Simulation Tools and Techniques. 11th International Conference, SIMUtools 2019, Chengdu, China, July 8--10, 2019, Proceedings},
        proceedings_a={SIMUTOOLS},
        year={2019},
        month={10},
        keywords={Network traffic Traffic estimation Software-defined network Optimization ARMA},
        doi={10.1007/978-3-030-32216-8_9}
    }
    
  • Renxiang Huang
    Huibin Jia
    Xing Huang
    Year: 2019
    A SDN-Based Network Traffic Estimating Algorithm in Power Telecommunication Network
    SIMUTOOLS
    Springer
    DOI: 10.1007/978-3-030-32216-8_9
Renxiang Huang1,*, Huibin Jia2, Xing Huang3
  • 1: Sichuan University of Arts and Science
  • 2: North China Electric Power University
  • 3: State Grid Liaoning Electric Power Company
*Contact email: wanddy@gmail.com

Abstract

Most of network management tasks in traffic engineering such as traffic scheduling, path planning, both of them are required the accurate and fine-grained network traffic. However, it is difficult to capture and estimate the volume of network traffic due to its time-varying nature. In this paper, we study the network traffic estimation scheme to estimate the fine-grained network traffic. Firstly, the network traffic is constructed as a time series and the autoregressive moving average (ARMA) method is used to characterize and model network traffic. Secondly, in order to decrease the estimation errors of the ARMA model, we use the optimization theory to adjust the estimation results. We construct an objective function with constraints. We find that objective function is an NP-hard problem, then we introduce a heuristic algorithm to find the optimization results. Finally, to evaluate the performance of our proposed scheme, we construct a simulation platform and compare our scheme with that of the other methods in an SDN simulation platform. The simulation results indicate that our approach is effective and our method can reflect the network traffic characteristics.