Multimedia Tools and Applications

, Volume 78, Issue 3, pp 3471–3492 | Cite as

Dynamic pricing with traffic engineering for adaptive video streaming over software-defined content delivery networking

  • Pingting Hao
  • Liang Hu
  • Kuo Zhao
  • Jingyan Jiang
  • Tong Li
  • Xilong CheEmail author


Multimedia content has become widespread in network traffic. The high volume of data and flexibility must be addressed to guarantee the quality of experience (QoE) in large-scale adaptive video streaming services. Despite the abundance of recently proposed strategies, most concentrate on improving different aspects of performance over user fairness and initiation. We propose Dynamic Pricing with Traffic Engineering (DPTE), a prototype that generates traffic distribution using a market-driven model. In DPTE, users specify required rates, and a price module gives the current value based on observation of the states of servers as well as networks. DPTE periodically runs a heuristic algorithm that selects the path with the appropriate pricing to guarantee the service based on the software-defined content delivery networking (SDCDN) platform. As a result, DPTE not only relies on pricing to reflect the objective properties from the performance perspective but also utilizes pricing rules to influence the choice of users. Evaluation results on Youtube data show that DPTE outperforms competitive pricing rules in most cases, including path utility, user satisfaction and revenue.


Content delivery network Software defined network Multimedia Pricing model Traffic engineering Network utility theory 



This work is funded by the National Key R&D Plan of China under Grant No. 2017YFA0604500, National Sci-Tech Support Plan of China under Grant No. 2014BAH02F00, by the National Natural Science Foundation of China under Grant No. 61701190, by the Youth Science Foundation of Jilin Province of China under Grant No. 20160520011JH and No. 20180520021JH, by Youth Sci-Tech Innovation Leader and Team Project of Jilin Province of China under Grant No. 20170519017JH, and by the Key Technology Innovation Cooperation Project of Government and University for the whole Industry Demonstration under Grant No. SXGJSF2017-4. Key scientific and technological R&D Plan of Jilin Province of China under Grant No. 20180201103GX.


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Pingting Hao
    • 1
  • Liang Hu
    • 1
  • Kuo Zhao
    • 1
  • Jingyan Jiang
    • 1
  • Tong Li
    • 2
  • Xilong Che
    • 1
    Email author
  1. 1.Department of Computer ScienceJiLin UniversityChangchunChina
  2. 2.Department of Computer ScienceGuangzhou UniversityGuangzhouChina

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