A Novel Long Term Traffic Forecast Algorithm

نویسندگان

  • Dongchen Zhang
  • Shoufeng Wang
  • Xiaoyan Xu
  • Xingzheng Li
  • Wenwen Yao
  • Tinglan Wang
چکیده

Data traffic raises dramatically in recent years. The burst of data demands for high capacity of communication networks. This brings more challenges for the industry. Forecast of traffic growth becomes important. Based on the traffic forecast, the industry can design a long-term strategy for communication development. To evaluate traffic forecast result, proper methodology is required. In this paper, a novel long term traffic forecast algorithm (LTTFA) is proposed.

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تاریخ انتشار 2014