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Collaborate Algorithms for the Multi-channel Program Download Problem in VOD Applications

  • Wenli Zhang
  • Lin Yang
  • Kepi Zhang
  • Chao PengEmail author
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 201)

Abstract

Video-on-demand (VOD) is a multimedia technology that allows users to watch video programs from a server flexibly at any time. In recent years, VOD applications are very popular in many networks, especially in internet of vehicles where video programs can often be collaboratively downloaded from multiple channels simultaneously. In this paper, we first study the Multi-Channel Program Download Problem (McPDP), which is to download a set of interested programs from different channels within limited time. We prove that McPDP is NP-complete by reduction from 3-SAT(3). For another version with neatly placed programs of equal length, the aligned multi-channel program download problem (AMcPDP), we present an algorithm by transforming it into a max-flow problem. Finally, we have also analyzed the performance of these proposed algorithms by simulation using MATLAB.

Keywords

Video-on-demand Multi-channel Program Download Problem NP-complete Scheduling algorithms 

References

  1. 1.
    Hanczewski, S., Stasiak, M.: Modeling of video on demand systems. In: Kwiecień, A., Gaj, P., Stera, P. (eds.) CN 2014. CCIS, vol. 431, pp. 233–242. Springer, Cham (2014). doi: 10.1007/978-3-319-07941-7_24 CrossRefGoogle Scholar
  2. 2.
    Miesler, L., Gehring, B., Hannich, F., Wüthrich, A.: User experience of video-on-demand applications for smart TVs: a case study. In: Marcus, A. (ed.) DUXU 2014. LNCS, vol. 8520, pp. 412–422. Springer, Cham (2014). doi: 10.1007/978-3-319-07638-6_40 Google Scholar
  3. 3.
    Atzori, L., De Natale, F.G.B., Di Gregorio, M., Giusto, D.D.: Multimedia information broadcasting using digital TV channels. IEEE Trans. Broadcast. 43(3), 242–251 (1997)CrossRefGoogle Scholar
  4. 4.
    Peng, C., Tan, Y., Xiong, N., Yang, L.T., Park, J.H., Kim, S.-S.: Adaptive video-on-demand broadcasting in ubiquitous computing environment. Pers. Ubiquit. Comput. 13(7), 479–488 (2009)CrossRefGoogle Scholar
  5. 5.
    Aggarwal, C.C., Wolf, J.L., Yu, P.S.: A permutation-based pyramid broadcasting scheme for video-on-demand systems. In: Proceedings of the International Conference on Multimedia Computing and Systems, pp. 118–126 (1996)Google Scholar
  6. 6.
    Almeroth, K.C., Ammar, M.H.: The use of multicast delivery to provide a scalable and interactive video-on-demand service. IEEE J. Sel. Areas Commun. 14(5), 1110–1122 (1996)CrossRefGoogle Scholar
  7. 7.
    Juhn, L., Tseng, L.: Harmonic broadcasting for video-on-demand service. IEEE Trans. Broadcast. 43(3), 268–271 (1997)CrossRefGoogle Scholar
  8. 8.
    Tian, C., Sun, J., Wu, W., Luo, Y.: Optimal bandwidth allocation for hybrid video-on-demand streaming with a distributed max flow algorithm. Comput. Netw. 91, 483–494 (2015)CrossRefGoogle Scholar
  9. 9.
    Peng, C., Zhou, J., Zhu, B., Zhu, H.: Complexity analysis and algorithms for the program download problem. J. Comb. Optim. 29(1), 216–227 (2015)MathSciNetCrossRefzbMATHGoogle Scholar
  10. 10.
    Xie, H., Boukerche, A., Loureiro, A.A.F.: MERVS: a novel multichannel error recovery video streaming protocol for vehicle ad hoc networks. IEEE Transaction on Vehicular Technology 65(2), 923–935 (2016)CrossRefGoogle Scholar
  11. 11.
    Yang, T., Liang, H., Cheng, N., Deng, R., Shen, X.: Efficient scheduling for video transmissions in maritime wireless communication networks. IEEE Transaction on Vehicular Technology 64(9), 4215–4229 (2015)CrossRefGoogle Scholar
  12. 12.
    Zaixin, L., Shi, Y., Weili, W., Bin, F.: Efficient data retrieval scheduling for multi-channel wireless data broadcast. In: Proceedings of the 31st IEEE International Conference on Computer Communications (INFOCOM), pp. 891–899 (2012)Google Scholar
  13. 13.
    Lu, Z., Wu, W., Fu, B.: Optimal data retrieval scheduling in the multi-channel data broadcast environments. IEEE Trans. Comput. 62(12), 2427–2439 (2013)MathSciNetCrossRefGoogle Scholar
  14. 14.
    Paris, J.-F., Carter, S., Long, D.D.E.: Efficient broadcasting protocols for video on demand. In: MASCOTS, pp. 127–132 (1998)Google Scholar
  15. 15.
    Aggarwal, V., Robert Calderbank, A., Gopalakrishnan, V., Jana, R., Ramakrishnan, K.K., Yu, F.: The effectiveness of intelligent scheduling for multicast video-on-demand. In: ACM Multimedia, pp. 421–430 (2009)Google Scholar
  16. 16.
    Darmann, A., Dcker, J.: Monotone 3-Sat-4 is NP-complete. CoRR abs/1603.07881 (2016)Google Scholar

Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2017

Authors and Affiliations

  1. 1.School of Computer Science and Software EngineeringEast China Normal UniversityShanghaiChina

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