Bayesian model-based traffic flow prediction scheme in software-defined optical networks

Wang Fei; Yang Junxiong

doi:10.13756/j.gtxyj.2014.05.004

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Bayesian model-based traffic flow prediction scheme in software-defined optical networks

- Bayesian model-based traffic flow prediction scheme in software-defined optical networks
- Study on Optical communication Issue 5, Pages: 11-13(2014)
- 作者机构：
  
  云南工商学院建筑工程学院
- 作者简介：
- 基金信息：
- DOI：10.13756/j.gtxyj.2014.05.004
  CLC： TN929.1
- Published：2014，
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[1]王非,杨俊雄.SDON中基于贝叶斯模型的流量预测机制[J].光通信研究,2014(05):11-13.

Wang Fei, Yang Junxiong. Bayesian model-based traffic flow prediction scheme in software-defined optical networks. [J]. (5):11-13(2014)
[1]王非,杨俊雄.SDON中基于贝叶斯模型的流量预测机制[J].光通信研究,2014(05):11-13. DOI： 10.13756/j.gtxyj.2014.05.004.

Wang Fei, Yang Junxiong. Bayesian model-based traffic flow prediction scheme in software-defined optical networks. [J]. (5):11-13(2014) DOI： 10.13756/j.gtxyj.2014.05.004.

摘要

SDON（软件定义光网络）是光网络发展的最新趋势。为了进一步提高SDON的智能化和对业务的动态支持

利用短期的业务流量特性预测较为长期的流量显得日益重要。文章提出了一种基于贝叶斯模型的流量预测机制

该机制充分利用贝叶斯模型对SDON的业务流量进行长期预测。仿真结果验证了该机制的准确性和有效性。

Abstract

The Software-Defined Optical Network（SDON）is the latest trend and orientation of the development of optical networks.In order to further improve its intelligentization and dynamic support to traffics

it becomes increasingly important to predict the longer-term traffic flow on the basis of the short-term traffic flow behavior.This article proposes a Bayesian Modelbased Traffic Prediction（BM-TP）scheme

which makes full use of the model to make long-term prediction of SDON traffic flow.Simulation results verify the accuracy and effectiveness of this scheme.

关键词

软件定义光网络贝叶斯模型流量预测

Keywords

SDONBayesian modeltraffic flow prediction

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Information and Communication Branch of State Grid Shanxi Electric Power Company

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