DOI QR코드

DOI QR Code

Optimizing Caching in a Patch Streaming Multimedia-on-Demand System

  • Bulti, Dinkisa Aga (Department of Electrical and Computer Engineering, Wolkite University) ;
  • Raimond, Kumudha (Department of Computer Science and Engineering, Karunya University)
  • Received : 2014.10.20
  • Accepted : 2015.07.05
  • Published : 2015.09.30

Abstract

In on-demand multimedia streaming systems, streaming techniques are usually combined with proxy caching to obtain better performance. The patch streaming technique has no start-up latency inherent to it, but requires extra bandwidth to deliver the media data in patch streams. This paper proposes a proxy caching technique which aims at reducing the bandwidth cost of the patch streaming technique. The proposed approach determines media prefixes with high patching cost and caches the appropriate media prefix at the proxy/local server. Herein the scheme is evaluated using a synthetically generated media access workload and its performance is compared with that of the popularity and prefix-aware interval caching scheme (the prefix part) and with that of patch streaming with no caching. The bandwidth saving, hit ratio and concurrent number of clients are used to compare the performance, and the proposed scheme is found to perform better for different caching capacities of the proxy server.

Keywords

References

  1. A. Dan, D. M. Dias, R. Mukherjee, D. Sitaram, and R. Tewari, "Buffering and caching in large-scale video servers," in Technologies for the Information Superhighway: Digest Of Papers (COMPCON'95), San Francisco, CA, 1995, pp. 217-224.
  2. J. Yu, C. T. Chou, X. Du, and T. Wang, "Internal popularity of streaming video and its implication on caching," in Proceedings of the 20th International Conference on Advanced Information Networking and Applications (AINA'06), Vienna, Austria, 2006.
  3. W. Tang, Y. Fu, L. Cherkasova, and A. Vahdat, "Modeling and generating realistic streaming media server workloads," Computer Networks, vol. 51, no. 1, pp. 336-356, 2007. https://doi.org/10.1016/j.comnet.2006.05.003
  4. K. Li, C. Xu, Y. Zhang, and Z. Wu, "Optimal prefix caching and data sharing strategy," in Proceedings of IEEE International Conference on Multimedia & Expo (ICME2008), Hannover, Germany, 2008, pp. 465-468.
  5. H. Ma and K. G. Shin, "Multicast video-on-demand services," ACM SIGCOMM Computer Communication Review, vol. 32, no. 1, pp. 31-43, 2002. https://doi.org/10.1145/510726.510729
  6. L. Golubchik, J. C. Lui, and R. R. Muntz, "Adaptive piggybacking: a novel technique for data sharing in video-ondemand storage servers," Multimedia System, vol. 4, no. 3, pp. 140-155, 1996. https://doi.org/10.1007/s005300050019
  7. K. A. Hua, Y. Cai, and S. Sheu, "Patching: a multicast technique for true video-on-demand services," in Proceedings of the 6th ACM International Conference on Multimedia, Bristol, UK, 1998, pp. 191-200.
  8. J. Choi, M. Yoo, and B. Mukherjee, "Efficient VoD streaming for broadband access networks," in Proceeding of IEEE Global Telecommunications Conference (GLOBECOM), New Orleans, LA, 2008, pp. 1-6.
  9. T. Kim, H. Bahn, and K. Koh, "Popularity-aware interval caching for multimedia streaming servers," Electronics Letters, vol. 39, no. 21, pp. 1555-1557, 2003. https://doi.org/10.1049/el:20030965
  10. O. Kwon, H. Bahn, and K. Koh, "Popularity and prefix aware interval caching for multimedia streaming servers," in Proceedings of 8th IEEE International Conference on Computer and Information Technology (CIT2008), Sydney, 2008, pp. 555-560.
  11. L. Wujuan, L. S. Yong, and Y. K. Leong, "A novel interval caching strategy for video-on-demand systems," in Proceedings of 14th IEEE International Conference on Networks (ICON'06), Singapore, 2006, pp. 1-5.
  12. T. R. Gopalakrishnan Nair and P. Jayarekha, "A strategy to enable prefix of multicast VoD through dynamic buffer allocation," International Journal of Computer Science Issues (IJCSI), vol. 7, no. 1, pp. 42-48, 2010.
  13. B. Chang, L. Dai, Y. Cui, and Y. Xue, "On feasibility of P2P on-demand streaming via empirical VoD user behavior analysis," in Proceedings of 28th International Conference on Distributed Computing Systems Workshops (ICDCS'08), Beijing, China, 2008, pp. 7-11.
  14. F. T. Johnsen, T. Hafsoe, and C. Griwodz, "Analysis of server workload and client interactions in a news-on-demand streaming system," in Proceedings of 8th IEEE International Symposium on Multimedia (ISM'06), San Diego, CA, 2006, pp. 724-727.
  15. L. Cherkasova and M. Gupta, "Analysis of enterprise media server workloads: access patterns, locality, content evolution, and rates of change," IEEE/ACM Transactions on Networking, vol. 12, no. 5, pp. 781-794, 2004. https://doi.org/10.1109/TNET.2004.836125
  16. Y. W. Wong and J. Y. B. Lee, "Recursive patching: an efficient technique for multicast video streaming, databases and information systems integration," in Proceedings of 5th International Conference on Enterprise Information Systems (ICEIS), Angers, France, 2003, pp. 306-312.
  17. T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein, Introduction to Algorithms, 2nd ed. Cambridge, MA: MIT Press, pp. 370-384, 2002.
  18. W. Tang, Y. Fu, L. Cherkasova, and A. Vahdat, "MediSyn: a synthetic streaming media service workload generator," in Proceedings of the 13th international workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV'03), Monterey, CA, 2003, pp. 12-21.
  19. G. Gursun, M. Crovella, and I. Matta, "Describing and forecasting video access patterns," in Proceedings of IEEE INFOCOM, Shanghai, China, 2011, pp. 16-20.
  20. Echo state networks, http://reservoir-computing.org/.
  21. T. Mezzano, "Echo state networks application on maze problems," M.Sc. thesis, Katholieke Universiteit Leuven, Faculty of Engineering Science, Leuven, Belgium, 2007.
  22. T. Wu, M. Timmers, D. D. Vleeschauwer, and W. V. Leekwijck, "On the use of reservoir computing in popularity prediction," in Proceedings of 2010 2nd International Conference on Evolving Internet (INTERNET), Valencia, Spain, 2010, pp. 19-24.

Cited by

  1. $\mathsf{REboost}$ : Improving Throughput in Wireless Networks Using Redundancy Elimination vol.21, pp.1, 2017, https://doi.org/10.1109/LCOMM.2016.2618798
  2. 5G Network Communication, Caching, and Computing Algorithms Based on the Two-Tier Game Model vol.40, pp.1, 2018, https://doi.org/10.4218/etrij.2017-0023