Skip to main content
Log in

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

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. (2016) Cisco visual networking index: global mobile data traffic forecast update, 2015-2020, white paper

  2. Adhikari VK, Guo Y, Hao F et al (2012) Unreeling netflix: understanding and improving multi-cdn movie delivery[C]//INFOCOM, 2012 proceedings IEEE. IEEE pp 1620–1628

  3. Benchaita W, Ghamri-Doudane S, Tixeuil S (2015) On the optimization of request routing for content delivery[J]. ACM SIGCOMM Comput Commun Rev 45(4):347–348

    Article  Google Scholar 

  4. Bhushan K, Gupta BB (2017) A novel approach to defend multimedia flash crowd in cloud environment[J]. Multimed Tools Appl 3:1–31

    Google Scholar 

  5. Bliznets I, Bliznets I, Kandula S et al (2016) Dynamic pricing and traffic engineering for timely inter-datacenter transfers[C]// conference on ACM SIGCOMM 2016 conference. ACM pp 73–86

  6. Cheng X, Dale C, Liu J (2008) Statistics and social network of YouTube videos[C]// international workshop on quality of service. IEEE pp 229–238

  7. Cloudfront (2017) [Online]. Available: http://aws.amazon.com/cn/cloudfront/

  8. Courcoubetis C, Weber R (2003) Pricing communication networks: economics, technology and modelling (Wiley Interscience series in systems and optimization)[M]. Wiley, New York

    Book  Google Scholar 

  9. Dobrian F, Sekar V, Awan A et al (2011) Understanding the impact of video quality on user engagement[C]//ACM SIGCOMM computer communication review. ACM 41(4):362–373

    Google Scholar 

  10. Egilmez HE, Tekalp AM (2014) Distributed QoS architectures for multimedia streaming over software defined networks[J]. IEEE Trans Multimed 16(6):1597–1609

    Article  Google Scholar 

  11. Egilmez HE, Dane ST, Bagci KT et al (2012) OpenQoS: an OpenFlow controller design for multimedia delivery with end-to-end quality of service over software-defined networks[C]// signal & information processing association summit and conference. IEEE pp 1–8

  12. Ercetin O, Tassiulas L (2005) Pricing strategies for differentiated services content delivery networks [J]. ACM Comput Netw 49(6):840–855

    Article  Google Scholar 

  13. Fan L, Lei X, Yang N et al (2016) Secure multiple amplify-and-forward relaying with cochannel interference[J]. IEEE J Sel Top Signal Process 10(8):1494–1505

    Article  Google Scholar 

  14. Fan L, Lei X, Yang N et al (2017) Secrecy cooperative networks with outdated relay selection over correlated fading channels[J]. IEEE Trans Veh Technol 66(8):7599–7603

    Article  Google Scholar 

  15. Gupta BB, Agrawal DP, Yamaguchi S (2016) Handbook of research on modern cryptographic solutions for computer and cyber security[M]. IGI Publishing, Hershey

  16. Hai AT, Hoceini S, Mellouk A et al (2013) QoE-based server selection for content distribution networks[J]. IEEE Trans Comput 99(11):2803–2815

    MathSciNet  MATH  Google Scholar 

  17. Hande P, Chiang M, Calderbank R et al (2009) Network pricing and rate allocation with content provider participation[C]// INFOCOM. IEEE pp 990–998

  18. Hosanagar K, Krishnan R, Smith M et al (2004) Optimal pricing of content delivery network (CDN) services[C]// proceedings of the, Hawaii international conference on system sciences. IEEE Comput Soc 7(9):10

    Google Scholar 

  19. Huang TY, Handigol N, Heller B et al (2012) Confused, timid, and unstable: picking a video streaming rate is hard[C]//proceedings of the 2012 ACM conference on internet measurement conference. ACM pp 225–238

  20. IBM support (2017) [Online]. Available: https://www.ibm.com/support/home/entry/portal/support

  21. Ibtihal M, Driss EO, Hassan N (2017) Homomorphic encryption as a Service for Outsourced Images in mobile cloud computing environment[J]. Int J Cloud Appl Comput 7(2):27–40

    Google Scholar 

  22. Jararweh Y, Alsmirat M, Al-Ayyoub M et al (2017) Software-defined system support for enabling ubiquitous mobile edge computing[J]. Comput J 60(10):1443–1457

    Article  Google Scholar 

  23. Jiang T, Chen X, Li J, Wong DS, Ma J, Liu JK (2015) Towards secure and reliable cloud storage against data re-outsourcing[J]. Fut Gener Comput Syst 52:86–94

    Article  Google Scholar 

  24. Khare V, Zhang B (2012) CDN Request routing to reduce network access cost[C]// IEEE, conference on local computer networks. IEEE Comput Soc pp 610–617

  25. Krishnan SS, Sitaraman RK (2013) Video stream quality impacts viewer behavior: inferring causality using quasi-experimental designs[J]. IEEE/ACM Trans Networking 21(6):2001–2014

    Article  Google Scholar 

  26. Kua J, Armitage G, Branch P (2017) A survey of rate adaptation techniques for dynamic adaptive streaming over HTTP[J]. IEEE Commun Surv Tutorials 19(3):1842–1866

    Article  Google Scholar 

  27. Lai X, Zou W, Xie D et al (2017) DF relaying networks with randomly distributed interferers[J]. IEEE Access 5:18909–18917

  28. Lin W, Xu SY, Li J et al (2015) Design and theoretical analysis of virtual machine placement algorithm based on peak workload characteristics[J]. Soft Comput 27(7):1–14

    Google Scholar 

  29. Lin W, Wu Z, Lin L, Wen A, Li J (2017) An ensemble random forest algorithm for insurance big data analysis[J]. IEEE Access 5:16568–16575

    Article  Google Scholar 

  30. Lin W, Xu S, He L, Li J (2017) Multi-resource scheduling and power simulation for cloud computing[J]. Inf Sci 397:168–186

    Article  Google Scholar 

  31. Liu B, Fan W, Xiao T et al (2015) Unsupervised dynamic fuzzy cognitive map[J]. Tsinghua Sci Technol 20(3):285–292

    Article  MathSciNet  Google Scholar 

  32. MaxCDN (2017) [Online]. Available: http://www.maxcdn.com/

  33. Memos VA, Psannis KE, Ishibashi Y et al (2018) An efficient algorithm for media-based surveillance system (EAMSuS) in IoT Smart City framework[J]. Futur Gener Comput Syst 83:619–628

    Article  Google Scholar 

  34. Meng W, Tischhauser E, Wang Q, Wang Y, Han J (2018) When intrusion detection meets blockchain technology: a review. IEEE Access 6:10179–10188

    Article  Google Scholar 

  35. Nam H, Kim KH, Kim JY et al (2014) Towards QoE-aware video streaming using SDN[C]// global communications conference. IEEE pp 1317–1322

  36. Odlyzko A (1999) Paris metro pricing for the internet[C]// ACM conference on electronic commerce. ACM pp 140–147

  37. Schwarz M, Sauer C, Daduna H et al (2006) M/M/1 queueing systems with inventory[J]. Queueing Syst 54(1):55–78

    Article  MathSciNet  Google Scholar 

  38. Sun Y, Yin X, Jiang J et al (2016) Cs2p: improving video bitrate selection and adaptation with data-driven throughput prediction[C]//proceedings of the 2016 conference on ACM SIGCOMM 2016 conference. ACM pp 272–285

  39. Szymaniak M, Pierre G, Steen MV (2003) Netairt: a flexible redirection system for apache[C]// Iadis international conference www/internet 2003, Icwi 2003, Algarve, Portugal, November. DBLP pp 435–442

  40. Tencent cloud (2017) [Online]. Available: https://www.qcloud.com/product/cdn

  41. Wang X, Tang S (2015) Bit-level soft-decision decoding of double and triple-parity reed-Solomon codes through binary hamming code constraints[J]. IEEE Commun Lett 19(2):135–138

    Article  Google Scholar 

  42. Wang X, Ma X, Bai B (2014) Design of efficiently encodable nonbinary LDPC codes for adaptive coded modulation[J]. SCIENCE CHINA Inf Sci 57(2):1–11

    MATH  Google Scholar 

  43. Wang Y, Li K, Li K (2017) Partition scheduling on heterogeneous multicore processors for multi-dimensional loops applications[J]. Int J Parallel Prog 45(4):827–852

    Article  Google Scholar 

  44. Xie G, Li Z, Kaafar MA et al (2017) Access types effect on internet video services and its implications on CDN caching[J]. IEEE Trans Circ Syst Video Technol 28(5):1183–1196

  45. Zhang Y, Cui G, Wang Y et al (2015) An optimization algorithm for service composition based on an improved FOA[J]. Tsinghua Sci Technol 20(1):90–99

    Article  MathSciNet  Google Scholar 

  46. Zhou J, Hu L, Wang F et al (2013) An efficient multidimensional fusion algorithm for IoT data based on partitioning[J]. Tsinghua Sci Technol 18(4):369–378

    Article  Google Scholar 

  47. Zkik K, Orhanou G, Hajji SE et al (2017) Secure mobile multi cloud architecture for authentication and data storage[J]. Int J Cloud Appl Comput 7(2):62–76

    Google Scholar 

Download references

Acknowledgments

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.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xilong Che.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hao, P., Hu, L., Zhao, K. et al. Dynamic pricing with traffic engineering for adaptive video streaming over software-defined content delivery networking. Multimed Tools Appl 78, 3471–3492 (2019). https://doi.org/10.1007/s11042-018-6111-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-018-6111-5

Keywords

Navigation