Open Access
Issue
ITM Web Conf.
Volume 21, 2018
Computing in Science and Technology (CST 2018)
Article Number 00016
Number of page(s) 14
DOI https://doi.org/10.1051/itmconf/20182100016
Published online 12 October 2018
  1. R. Pantos, W. May, HTTP live streaming, IETF, Informational Internet-Draft 2582, (2011). [Google Scholar]
  2. M. Seufert, et al., A survey on quality of experience of HTTP adaptive streaming, IEEE Commun Surveys Tuts, 17(1): 469–492, (2015). [CrossRef] [Google Scholar]
  3. N. A. Saqib, Y. Shakeel, M. A. Khan, H. Mehmood, M. Zia, An effective empirical approach to VoIP traffic classification. Turk J Elec Eng & Comp Sci, 25: 888–900, (2017). [CrossRef] [Google Scholar]
  4. C. Sieber, A. Blenk, M. Hinteregger, W. Kellerer, The cost of aggressive HTTP adaptive streaming: Quantifying YouTube's redundant traffic, In Proc. IFIP/IEEE IM’15, pp. 1261–1267, (2015). [Google Scholar]
  5. E. Essaili E, et al, QoE-based traffic and resource management for adaptive HTTP video delivery in LTE, IEEE Trans Circuits Syst Video Technol, 25(6): 988–1001, (2015). [CrossRef] [Google Scholar]
  6. J. Samain, G. Carofiglio, L. Muscariello, et al., Dynamic Adaptive Video Streaming: Towards a Systematic Comparison of ICN and TCP/IP, IEEE transactions on Multimedia, 19(10): 2166–2181, (2017). [CrossRef] [Google Scholar]
  7. Cisco. Visual networking index: Global mobile data traffic forecast update, 2016–2021, White Paper, (2017). [Google Scholar]
  8. I. Santos-Gonalez, A. Rivero-Garcia, J. Molina-Gil, P. Caballero-Gil, Implementation and Analysis of Real-Time Streaming Protocols. Reindl LM, Ed. Sensors (Basel, Switzerland), 17(4): 846, (2017). [CrossRef] [Google Scholar]
  9. T. Zinner, O. Abboud, O. Hohlfeld, T. Hossfeld, P. Tran-Gia, Towards QoE management for scalable video streaming; Proc. of ITC Spec. Sem. on Multimedia Applications-Traffic, Performance and QoE; Miyazaki, Japan, pp. 64–69, (2010). [Google Scholar]
  10. W. W. Leland, M. S. Taqqu, W. Willinger, D. V. Wilson, On the self-similar nature of ethernet traffic (extended version). IEEE/ACM Trans on Netw, 2(1):1–15, (1994). [CrossRef] [Google Scholar]
  11. S. Vig, Network Congestion as an Emergent Phenomena in Internet Traffic, (2011). [Google Scholar]
  12. E. Manley, T. Cheng, Understanding Road Congestion as an Emergent Property of Traffic Networks, Proc. of 14th World Multi-conference on Systemics, Cybernetics and Informatics, pp. 25–34, (2010). [Google Scholar]
  13. A. Popescu, Traffic self-similarity, In Proc of the IEEE ICT2001, pp. 20–24, (2001). [Google Scholar]
  14. M. Da Silva, A. Correia, Transmission Techniques for Emergent Multicast and Broadcast Systems, CRC Press, (2010). [CrossRef] [Google Scholar]
  15. R. Wittmann, Multicast Communication: Protocols & Applications, MK, (20010. [Google Scholar]
  16. S. S. Manvi, M. S Kakkasager, Multicast routing in mobile ad hoc networks by using a multiagent system, Infn Scien, 178(6): 1611–1628, (2008). [CrossRef] [Google Scholar]
  17. B. Williamson, Developing IP Multicast Networks, Volume I, Cisco Press, (1999). [Google Scholar]
  18. E. Rosenberg, A Primer of Multicast Routing, Springer, (2012). [CrossRef] [Google Scholar]
  19. M. Mazurek, P. Dymora. Network Anomaly Detection Based on the Statistical Self-similarity Factor, Analysis and Simulation of Electrical and Computer Systems, LNEE; 324: 271–287, (2015). [Google Scholar]
  20. P. Dymora, M. Mazurek, K. Zelazny, Operating system efficiency evaluation on the base of measurements analysis with the use of non-extensive statistics elements, Annales UMCS, Informatica, 14(3): 65–75, (2014). [Google Scholar]
  21. B. B. Mandelbrot, J.W. van Ness, Fractional Brownian Motions, Fractional Noises and Applications. SIAM Review, 10: 422–437, (1968). [Google Scholar]
  22. M. Mazurek, P. Dymora, Network anomaly detection based on the statistical self-similarity factor for HTTP protocol, Electr Rev, 90(1): 127–130, (2014). [Google Scholar]
  23. R. J. Adler, R. E. Feldman, M. S. Taqqu, A Practical Guide to Heavy Tails: Statistical Techniques and Applications (Eds.). Birkhauser, Boston, (1998). [Google Scholar]
  24. https://www.juniper.net/documentation/en\_US/junos/topics/concept/multicast-pim-overview.html, (2018). [Google Scholar]
  25. http://alumni.cs.ucr.edu/~tkarag/Selfis/Selfis.html, (2018). [Google Scholar]
  26. https://project.inria.fr/fraclab/, (2018). [Google Scholar]

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