International Conference on Multimedia Modeling

MultiMedia Modeling pp 100-113

NEWSMAN: Uploading Videos over Adaptive Middleboxes to News Servers in Weak Network Infrastructures

  • Rajiv Ratn Shah
  • Mohamed Hefeeda
  • Roger Zimmermann
  • Khaled Harras
  • Cheng-Hsin Hsu
  • Yi Yu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9516)

Abstract

An interesting recent trend, enabled by the ubiquitous availability of mobile devices, is that regular citizens report events which news providers then disseminate, e.g., CNN iReport. Often such news are captured in places with very weak network infrastructures and it is imperative that a citizen journalist can quickly and reliably upload videos in the face of slow, unstable, and intermittent Internet access. We envision that some middleboxes are deployed to collect these videos over energy-efficient short-range wireless networks. Multiple videos may need to be prioritized, and then optimally transcoded and scheduled. In this study we introduce an adaptive middlebox design, called NEWSMAN, to support citizen journalists. NEWSMAN jointly considers two aspects under varying network conditions: (i) choosing the optimal transcoding parameters, and (ii) determining the uploading schedule for news videos. We design, implement, and evaluate an efficient scheduling algorithm to maximize a user-specified objective function. We conduct a series of experiments using trace-driven simulations, which confirm that our approach is practical and performs well. For instance, NEWSMAN outperforms the existing algorithms (i) by 12 times in terms of system utility (i.e., sum of utilities of all uploaded videos), and (ii) by 4 times in terms of the number of videos uploaded before their deadline.

Keywords

News reporting News scheduling Adaptive transmission Video transcoding Multimedia information systems Information systems applications 

References

  1. 1.
    iReport at 5: Nearly 900,000 contributors worldwide, July 2012. http://www.niemanlab.org/2011/08/ireport-at-5-nearly-900000-contributors-worldwide/. Accessed on March 2015
  2. 2.
    Meet the million: 999,999 iReporters + you! July 2012. http://ireport.cnn.com/blogs/ireport-blog/2012/01/23/meet-the-million-999999-ireporters-you. Accessed on March 2015
  3. 3.
    Abba, H.A., Shah, S.N.M., Zakaria, N.B., Pal, A.J.: Deadline based performance evaluation of job scheduling algorithms. In: CyberC, pp. 106–110. IEEE (2012)Google Scholar
  4. 4.
    Bhattacharjee, S., Cheng, W.C., Chou, C.-F., Golubchik, L., Khuller, S.: Bistro: a framework for building scalable wide-area upload applications. ACM SIGMETRICS Perform. Eval. Rev. 28(2), 29–35 (2000)CrossRefGoogle Scholar
  5. 5.
    Chen, S., Tong, L., He, T.: Optimal deadline scheduling with commitment. In: ALLERTON, pp. 111–118. IEEE (2011)Google Scholar
  6. 6.
    Hefeeda, M., Hsu, C.-H.: On burst transmission scheduling in mobile tv broadcast networks. IEEE/ACM Trans. Networking (TON) 18(2), 610–623 (2010)CrossRefGoogle Scholar
  7. 7.
    Jokhio, F., Ashraf, A., Lafond, S., Porres, I., Lilius, J.: Prediction-based dynamic resource allocation for video transcoding in cloud computing. In: PDP, pp. 254–261. IEEE (2013)Google Scholar
  8. 8.
    Lacy, S., Atwater, T., Qin, X., Powers, A.: Cost and competition in the adoption of satellite news gathering technology. J. Media Econ. 1(1), 51–59 (1988)CrossRefGoogle Scholar
  9. 9.
    Lambert, P., De Neve, W., De Neve, P., Moerman, I., Demeester, P., Van de Walle, R.: Rate-distortion performance of H. 264/AVC compared to state-of-the-art video codecs. IEEE Trans. Circuits Syst. Video Technol. 16(1), 134–140 (2006)CrossRefGoogle Scholar
  10. 10.
    Li, Z., Huang, Y., Liu, G., Wang, F., Zhang, Z.-L., Dai, Y.: Cloud transcoder: bridging the format and resolution gap between internet videos and mobile devices. In: NOSSDAV, pp. 33–38. ACM (2012)Google Scholar
  11. 11.
    Liang, C., Guo, Y., Liu, Y.: Is random scheduling sufficient in P2P video streaming? In: International Conference on Distributed Computing Systems, pp. 53–60. IEEE (2008)Google Scholar
  12. 12.
    Liu, C.L., Layland, J.W.: Scheduling algorithms for multiprogramming in a hard-real-time environment. J. ACM (JACM) 20(1), 46–61 (1973)MATHMathSciNetCrossRefGoogle Scholar
  13. 13.
    Livingston, S., Van Belle, D.A.: The effects of satellite technology on newsgathering from remote locations. Political Commun. 22(1), 45–62 (2005)CrossRefGoogle Scholar
  14. 14.
    Recommendation ITU-T P.910. Subjective video quality assessment methods for multimedia applications (2008)Google Scholar
  15. 15.
    Shaikh, A.D., Jain, M., Rawat, M., Shah, R.R., Kumar, M.: Improving accuracy of SMS based FAQ retrieval system. In: Majumder, P., Mitra, M., Bhattacharyya, P., Subramaniam, L.V., Contractor, D., Rosso, P. (eds.) FIRE 2010 and 2011. LNCS, vol. 7536, pp. 142–156. Springer, Heidelberg (2013) CrossRefGoogle Scholar
  16. 16.
    Shaikh, A.D., Shah, R.R., Shaikh, R.: SMS based FAQ retrieval for Hindi, English and Malayalam. In: Forum on Information Retrieval Evaluation, p. 9. ACM (2013)Google Scholar
  17. 17.
    Tirumala, A., Qin, F., Dugan, J., Ferguson, J., Gibbs, K.: Iperf: the TCP/UDP bandwidth measurement tool (2005). http://dast.nlanr.net/Projects/Iperf/
  18. 18.
    Webster, A.A., Jones, C.T., Pinson, M.H., Voran, S.D., Wolf, S.: Objective video quality assessment system based on human perception. In: IS&T/SPIE’s Symposium on Electronic Imaging: Science and Technology, pp. 15–26. SPIE (1993)Google Scholar
  19. 19.
    Xie, D., Qian, B., Peng, Y., Chen, T.: A model of job scheduling with deadline for video-on-demand system. In: WISM, pp. 661–668. IEEE (2009)Google Scholar
  20. 20.
    Zhang, M., Wong, J., Tavanapong, W., Oh, J., de Groen, P.: Deadline-constrained media uploading systems. Multimedia Tools Appl. 38(1), 51–74 (2008)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Rajiv Ratn Shah
    • 1
  • Mohamed Hefeeda
    • 2
  • Roger Zimmermann
    • 1
  • Khaled Harras
    • 3
  • Cheng-Hsin Hsu
    • 4
  • Yi Yu
    • 5
  1. 1.National University of SingaporeSingaporeSingapore
  2. 2.Qatar Computing Research InstituteDohaQatar
  3. 3.CMU in QatarDohaQatar
  4. 4.National Tsinghua UniversityHsinchuTaiwan
  5. 5.National Institute of InformaticsTokyoJapan

Personalised recommendations