Skip to main content

Reducing Video Transmission Cost of the Cloud Service Provider with QoS-Guaranteed

  • Conference paper
  • First Online:
Data Science (ICPCSEE 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1628))

  • 622 Accesses

Abstract

With the advancement of cloud computing technology, many service providers are combining with cloud service providers to build a highly available streaming video-on-demand cloud platform and provide video services to end users. Generally, cloud service providers deploy many edge cloud CDN nodes in different geographic areas and provide video services to end users. However, when an end-user wants to watch certain videos and request video resources from surrounding edge cloud CDN nodes, the edge cloud CDN node will request missing video clips from other cloud nodes. Therefore, this will generate a large amount of additional video transmission costs and reduce the quality of service of the cloud service provider. To reduce or even minimize the video transmission cost of edge cloud CDN nodes while ensuring the quality of service (QoS). We designed a video transmission algorithm called Netdmc to ensure transmission quality. The algorithm can be divided into two parts. The first part is a low-latency video request algorithm based on ensuring service quality, and the second part is a video request algorithm based on minimizing video transmission costs. The simulation results demonstrate that the Netdmc algorithm can effectively reduce the cost of cloud service providers and ensure the quality of video services.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Zhu, J., Zheng, Z., Zhou, Y., Lyu, M.R.: Scaling service-oriented applications into geo-distributed clouds. In: 2013 IEEE Seventh International Symposium on Service-Oriented System Engineering, pp. 335–340 (2013)

    Google Scholar 

  2. Cherkasova, L.: Optimizing the reliable distribution of large files within CDNs. In: 10th IEEE Symposium on Computers and Communications (ISCC 2005), pp. 692–697 (2005)

    Google Scholar 

  3. Mahimkar, A., et al.: Bandwidth on demand for inter-data center communication. In: Proceedings of the 10th ACM Workshop on Hot Topics in Networks, pp. 1–6 (2011)

    Google Scholar 

  4. Jiao, L., Li, J., Xu, T., Du, W., Fu, X.: Optimizing cost for online social networks on geo-distributed clouds. IEEE/ACM Trans. Networking 24, 99–112 (2014)

    Article  Google Scholar 

  5. Zhang, J., Zhang, Y.: QoS-awareness peer coordination control for topology-converging P2P live streaming. Multimedia Tools Appl. 76(22), 23835–23858 (2016). https://doi.org/10.1007/s11042-016-4092-9

    Article  Google Scholar 

  6. Dong, X., Laiping, Z., Zhou, X., Li, K., Qiu, T., Guo, D.: An online cost-efficient transmission scheme for information-agnostic traffic in inter-datacenter networks. IEEE Trans. Cloud Comput. 10(1), 202–215 (2019)

    Article  Google Scholar 

  7. Golubchik, L., Khuller, S., Mukherjee, K., Yao, Y.: To send or not to send: reducing the cost of data transmission. In: 2013 Proceedings IEEE INFOCOM, pp. 2472–2478 (2013)

    Google Scholar 

  8. Borst, S., Gupta, V., Walid, A.: Distributed caching algorithms for content distribution networks. In: 2010 Proceedings IEEE INFOCOM, pp. 1–9 (2010)

    Google Scholar 

  9. Chu, W., Wang, L., Xie, H., Zhang, Z.-L., Jiang, Z.: Network delay guarantee for differentiated services in content-centric networking. Comput. Commun. 76, 54–66 (2016)

    Article  Google Scholar 

  10. Amble, M.M., Parag, P., Shakkottai, S., Ying, L.: Content-aware caching and traffic management in content distribution networks. In: IEEE (2011)

    Google Scholar 

  11. Greenberg, A., Hamilton, J., Maltz, D.A., Patel, P.: The cost of a cloud: research problems in data center networks, vol. 39, pp. 68–73. ACM New York, NY, USA (2008)

    Google Scholar 

  12. Chandy, J.A.: A generalized replica placement strategy to optimize latency in a wide area distributed storage system. In: Proceedings of the 2008 International Workshop on Data-Aware Distributed Computing, pp. 49–54 (2008)

    Google Scholar 

  13. Li, B., Zhang, X., Liu, J., Yum, T.-S.P.: Coolstreaming: a data-driven overlay network for efficient live media streaming. In: Proceedings of IEEE INFOCOM 2005 (2005)

    Google Scholar 

  14. Wiegand, T., Sullivan, G.J., Bjontegaard, G., Luthra, A.: Overview of the H. 264/AVC video coding standard. IEEE Trans. Circuits Syst. Video Technol. 13, 560–576 (2003)

    Article  Google Scholar 

  15. Shorfuzzaman, M., Graham, P., Eskicioglu, R.: Distributed placement of replicas in hierarchical data grids with user and system qos constraints. In: 2011 International Conference on P2P, Parallel, Grid, Cloud and Internet Computing, pp. 177–186 (2011)

    Google Scholar 

  16. Zhang, Z., Zhang, M., Greenberg, A.G., Hu, Y.C., Mahajan, R., Christian, B.: Optimizing cost and performance in online service provider networks. In: NSDI, pp. 33–48 (2010)

    Google Scholar 

  17. Shen, Y., Hsu, C.-H., Hefeeda, M.: Efficient algorithms for multi-sender data transmission in swarm-based peer-to-peer streaming systems. IEEE Trans. Multimedia 13, 762–775 (2011)

    Article  Google Scholar 

  18. Hu, H., et al.: Community based effective social video contents placement in cloud centric CDN network. In: 2014 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6 (2014)

    Google Scholar 

  19. Wang, Z., et al.: Propagation-based social-aware replication for social video contents. In: Proceedings of the 20th ACM International Conference on Multimedia, pp. 29–38 (2012)

    Google Scholar 

  20. Liu, G., Shen, H., Chandler, H.: Selective data replication for online social networks with distributed datacenters. IEEE Trans. Parallel Distrib. Syst. 27, 2377–2393 (2015)

    Article  Google Scholar 

  21. de Almeida, D.F., Yen, J., Aibin, M.: Content delivery networks-q-learning approach for optimization of the network cost and the cache hit ratio. In: 2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), pp. 1–5 (2020)

    Google Scholar 

  22. Ding, C., Zhou, A., Huang, J., Liu, Y., Wang, S.: ECDU: an edge content delivery and update framework in mobile edge computing. EURASIP J. Wirel. Commun. Netw. 2019(1), 1–9 (2019). https://doi.org/10.1186/s13638-019-1590-2

    Article  Google Scholar 

  23. Triukose, S., Rabinovich, M.: Client-centric content delivery network. In: 2016 Fourth IEEE Workshop on Hot Topics in Web Systems and Technologies (HotWeb), pp. 1–6 (2016)

    Google Scholar 

Download references

Acknowledgment

This research was supported by the national key research and development program of China (No. 2020YFF0305300), National Natural Science Foundation (No. 61762029, No. 61662012, No. U1811264), Guangxi Key Laboratory of Trusted Software (No. kx201726).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yemin Sun .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Liu, P., Sun, Y., Huang, K., Huang, G., Yu, Z. (2022). Reducing Video Transmission Cost of the Cloud Service Provider with QoS-Guaranteed. In: Wang, Y., Zhu, G., Han, Q., Wang, H., Song, X., Lu, Z. (eds) Data Science. ICPCSEE 2022. Communications in Computer and Information Science, vol 1628. Springer, Singapore. https://doi.org/10.1007/978-981-19-5194-7_29

Download citation

  • DOI: https://doi.org/10.1007/978-981-19-5194-7_29

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-5193-0

  • Online ISBN: 978-981-19-5194-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics