Client-Driven Price Selection for Scalable Video Streaming with Advertisements

  • Musab S. Al-Hadrusi
  • Nabil J. Sarhan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7131)

Abstract

This paper considers the scalable delivery framework of streaming video content with advertisements. In this framework, the revenues generated from the ads are used to subsidize the cost and thus attract more clients. We analyze a predictive scheme that provides clients with multiple price options, each with a certain number of expected viewed ads. The price depends on the royalty fee of the requested video, its delivery cost based on the current system state, the applied scheduling policy, and the number of viewed ads. The price is lower when the number of viewed ads is larger.

Keywords

Media streaming periodic broadcasting pricing scheduling stream merging waiting-time prediction 
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References

  1. 1.
    Aggarwal, C.C., Wolf, J.L., Yu, P.S.: The maximum factor queue length batching scheme for Video-on-Demand systems. IEEE Trans. on Computers 50(2), 97–110 (2001)CrossRefGoogle Scholar
  2. 2.
    Al-Hadrusi, M., Sarhan, N.J.: A scalable delivery framework and a pricing model for streaming media with advertisements. In: Proc. of SPIE/ACM Multimedia Computing and Networking Conference, MMCN (Januray 2008)Google Scholar
  3. 3.
    Cai, Y., Hua, K.A.: An efficient bandwidth-sharing technique for true video on demand systems. In: Proc. of ACM Multimedia, pp. 211–214 (October 1999)Google Scholar
  4. 4.
    Dan, A., Sitaram, D., Shahabuddin, P.: Scheduling policies for an on-demand video server with batching. In: Proc. of ACM Multimedia, pp. 391–398 (October 1994)Google Scholar
  5. 5.
    Eager, D.L., Vernon, M.K., Zahorjan, J.: Optimal and efficient merging schedules for Video-on-Demand servers. In: Proc. of ACM Multimedia, pp. 199–202 (October 1999)Google Scholar
  6. 6.
    Eager, D.L., Vernon, M.K., Zahorjan, J.: Minimizing bandwidth requirements for on-demand data delivery. IEEE Trans. on Knowledge and Data Engineering 13(5), 742–757 (2001)CrossRefGoogle Scholar
  7. 7.
    Gao, L., Kurose, J., Towsley, D.: Efficient schemes for broadcasting popular videos. In: Proc. of the Int’l Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV) (July 1998)Google Scholar
  8. 8.
    Gill, P., Shi, L., Mahanti, A., Li, Z., Eager, D.: Scalable on-demand media streaming for heterogeneous clients. ACM Transactions on Multimedia Computing, Communications, and Applications (ACM TOMCCAP) 5(1), 1–24 (2008)CrossRefGoogle Scholar
  9. 9.
    Hu, A.: Video-on-Demand broadcasting protocols: A comprehensive study. In: Proc. of IEEE INFOCOM (April 2001)Google Scholar
  10. 10.
    Hua, K.A., Cai, Y., Sheu, S.: Patching: A multicast technique for true Video-on-Demand services. In: Proc. of ACM Multimedia, pp. 191–200 (1998)Google Scholar
  11. 11.
    Huang, C., Janakiraman, R., Xu, L.: Loss-resilient on-demand media streaming using priority encoding. In: Proc. of ACM Multimedia, pp. 152–159 (October 2004)Google Scholar
  12. 12.
    Jagannathan, S., Almeroth, K.C.: The dynamics of price, revenue, and system utilization. In: Proc. of the IFIP/IEEE International Conference on Management of Multimedia Networks and Services, pp. 329–344 (2001)Google Scholar
  13. 13.
    Ma, H., Shin, G.K., Wu, W.: Best-effort patching for multicast true VoD service. Multimedia Tools Appl. 26(1), 101–122 (2005)CrossRefGoogle Scholar
  14. 14.
    Rayburn, D.: Streaming and Digital Media: Understanding the Business and Technology. Focal Press (2007)Google Scholar
  15. 15.
    Rocha, M., Maia, M., Cunha, I., Almeida, J., Campos, S.: Scalable media streaming to interactive users. In: Proc. of ACM Multimedia, pp. 966–975 (November 2005)Google Scholar
  16. 16.
    Sarhan, N.J., Das, C.R.: Caching and scheduling in NAD-based multimedia servers. IEEE Trans. on Parallel and Distributed Systems 15(10), 921–933 (2004)CrossRefGoogle Scholar
  17. 17.
    Sarhan, N.J., Al-Hadrusi, M.: Waiting-time prediction and QoS-based pricing for video streaming with advertisements. In: Proc. of IEEE International Symposium on Multimedia, ISM (December 2010)Google Scholar
  18. 18.
    Sarhan, N.J., Das, C.R.: A New Class of Scheduling Policies for Providing Time of Service Guarantees in Video-on-Demand Servers. In: Vicente, J.B., Hutchison, D. (eds.) MMNS 2004. LNCS, vol. 3271, pp. 127–139. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  19. 19.
    Sarhan, N.J., Qudah, B.: Efficient cost-based scheduling for scalable media streaming. In: Proc. of Multimedia Computing and Networking Conf., MMCN (January 2007)Google Scholar
  20. 20.
    Shi, L., Sessini, P., Mahanti, A., Li, Z., Eager, D.L.: Scalable streaming for heterogeneous clients. In: Proc. of ACM Multimedia, pp. 337–346 (October 2006)Google Scholar
  21. 21.
    Tantaoui, M.A., Hua, K.A., Do, T.T.: Broadcatch: A periodic broadcast technique for heterogeneous Video-on-Demand. IEEE Trans. on Broadcasting 50(3) (September 2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Musab S. Al-Hadrusi
    • 1
  • Nabil J. Sarhan
    • 1
  1. 1.Department of Electrical and Computer EngineeringWayne State UniversityDetroitUSA

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