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Performance Analysis of IPv4 and IPv6 Internet Traffic


Affiliations
1 Department of Electronics and Telecommunication Engineering, Pune Institute of Computer Technology, India
2 Department of Electronics and Telecommunication Engineering, Sinhgad College of Engineering, India
     

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The gigantic growth of the internet communication technology has illustrated its value and benefits to private businesses, government organizations, worldwide professionals, academic institutes and individuals over the past few years. The size and range of computing devices connected to the internet, substantially increased because of IPv6 and offers the potential to establish a much more powerful internet compared to the IPv4. IPv6 developed by the IETF to deal with a shortage of IP addresses under IPv4. New features of IPv6 enhance packet processing speeds over routers, switches and end systems. These improved features will have different traffic characteristics than IPv4. The internet traffic which was earlier assumed as Poisson is now shown to have fractal characteristics as; heavy tailedness, self-similarity and long range dependency. Internet traffic showing above characteristics are found to have burstiness at multiple timescales. This behavior impacts network performance and degrades it substantially. It also increases complexity for network design and create difficulties to maintain desired QoS. IPv4 traffic has been well established as self-similar traffic. Nowadays, IPv6 forming a larger share of the internet traffic and it is pivotal to asses IPv6 with regards to fractal behavior. This will enable network designers to do necessary changes in the existing network to reconcile with IPv6. In this paper we compared IPv4 and IPv6 with respect to fractal behavioral characteristics. It is found that IPv6 shows higher degree of heavy tailedness, higher values of Hurst parameter values, higher fractal dimension values i.e. it is more self-similar, greater autocorrelation achieved even at larger lag and thus showing more burstiness.

Keywords

IPv4, IPv6, Self-Similarity, Long Range Dependence, Heavy Tailedness, Burstiness.
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  • Mark E. Crovella and Azer Bestavros, “Self-Similarity in World Wide Web Traffic: Evidence and Possible Causes”, IEEE/ACM Transactions on Networking, Vol. 5, No. 6, pp. 835-846, 1997.

  • W. Willinger, M.S. Taqqu, R. Sherman and D.V. Wilson. “Self-Similarity Through High-Variability: Statistical Analysis of Ethernet LAN Traffic at the Source Level”, IEEE/ACM Transactions on Networking, Vol. 5, No. 1, pp. 71-86, 2002.

  • W.E. Leland, M.S. Taqqu, W. Willinger and D.V. Wilson, “On the Self-Similar Nature of Ethernet Traffic (extended version)”, IEEE/ACM Transactions on Networking, Vol. 2, No. 1, pp. 1-15, 1994.

  • Wei-Bo Gong, Yong Liu, Vishal Misra and Don Towsley, “Self-Similarity and Long Range Dependence on the Internet: A Second Look at the Evidence, Origins and Implications”, Computer Networks, Vol. 48, No. 3, pp. 377-399, 2005.

  • Kihong Park, Gitae Kim and Mark Crovella, “On the Relationship between File Sizes, Transport Protocols, and Self-Similar Network Traffic”, Proceedings of the 4th International Conference on Network Protocols, pp. 171-180, 1996.

  • Vern Paxson and Sally Floyd, “Wide-Area Traffic: The Failure of Poisson Modeling”, IEEE/ACM Transactions on Networking, Vol. 3, No. 3, pp. 226-244, 1995.

  • Benoit B. Mandelbrot, “The Fractal Geometry of Nature”, W.H. Freeman and Company, 1982.

  • http://mawi.wide.ad.jp/mawi/.

  • Internet Protocol, Version 6 (IPv6) Specification, 1995, Available at https://tools.ietf.org/html/rfc1883

  • M. Goncalves and K. Niles, “IPv6 Networks”, New York: McGraw-Hill, 1998.

  • Internet Protocol Version 4 (IPv4) Specification, IETF RFC 791, 1981, Available at https://tools.ietf.org/html/rfc791

  • Fayez Gebali, “Analysis of Computer and Communication Networks”, Springer US, 2008.

  • T.W. Anderson and D.A. Darling, “Asymptotic Theory of Certain ‘Goodness-of-Fit’ Criteria based on Stochastic Processes”, The Annals of Mathematical Statistics, Vol. 23, No. 2, pp. 193-212, 1952.

  • Chi squared test, Available at, http://mathworld.wolfram.com/Chi-SquaredTest.html.

  • Balakrishnan Chandrasekaran, “Survey of Network Traffic Models”, Student Project Report, Department of Computer Science and Engineering, Washington University, St. Louis, 2015.

  • Tarek Sobh, Khaled Elleithy, Ausif Mahmood and Mohamed Karim, Eds., “Innovative Algorithms and Techniques in Automation, Industrial Electronics and Telecommunications”, Springer, 2007.

  • Thomas Karagiannis and Michalis Faloutsos, “SELFIS: A Tool for Self-Similarity and Long-Range Dependence Analysis”, Proceedings of 1st Workshop on Fractals and Self-Similarity in Data Mining: Issues and Approaches, 2002.

  • F. Cervantes-De la Torre, J.I. González-Trejo, C.A. Real-Ramirez and L.F. Hoyos-Reyes, “Fractal Dimension Algorithms and their Application to Time Series Associated with Natural Phenomena”, Journal of Physics: Conference Series, Vol. 475, No. 1, pp. 1-10, 2013.

  • Cebrail Ciflikli, Ali Gezer, A. Tuncay Ozsahin, and Oznur Ozkasap, “BitTorrent Packet Traffic Features over IPv6 and IPv4, Simulation Modelling Practice and Theory”, Simulation Modelling Practice and Theory, Vol. 18, No. 9, pp. 1214-1224, 2010.

  • Kuan-Ta Chen, Polly Huang and Chin-Laung Lei, “Game Traffic Analysis: An MMORPG Perspective”, Computer Networks, Vol. 50, No. 16, pp. 3002-3023, 2006.

  • C. Jaiswal Rupesh and D. Lokhande Shashikant, “Measurement, Modelling and Analysis of HTTP Web Traffic”, International Conference on Communication and Computing, 2014.

  • http://www.census.gov/main/www/popclock.html

  • http://blogs.cisco.com/news/the-internet-of-things-infographic/

  • Cebrail Ciflikli, Ali Gezer and A. Tuncay Ozsahin, “Packet Traffic Features of IPv6 and IPv4 Protocol Traffic”, Turkish Journal of Electrical Engineering & Computer Sciences, Vol. 20, No. 5, pp. 727-749, 2012.

  • Chunmei Zhu, Yu Wang, Yan Zhang and Weiling Wu, “Different Behavioral Characteristics of Web Traffic between Wireless and Wire IP Network”, Proceedings of International Conference on Communication Technology, Vol. 1, pp. 267-271, 2003.


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  • Performance Analysis of IPv4 and IPv6 Internet Traffic

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Authors

Rupesh Jaiswal
Department of Electronics and Telecommunication Engineering, Pune Institute of Computer Technology, India
Shashikant Lokhande
Department of Electronics and Telecommunication Engineering, Sinhgad College of Engineering, India
Anuj Bakre
Department of Electronics and Telecommunication Engineering, Pune Institute of Computer Technology, India
Kishor Gutte
Department of Electronics and Telecommunication Engineering, Pune Institute of Computer Technology, India

Abstract


The gigantic growth of the internet communication technology has illustrated its value and benefits to private businesses, government organizations, worldwide professionals, academic institutes and individuals over the past few years. The size and range of computing devices connected to the internet, substantially increased because of IPv6 and offers the potential to establish a much more powerful internet compared to the IPv4. IPv6 developed by the IETF to deal with a shortage of IP addresses under IPv4. New features of IPv6 enhance packet processing speeds over routers, switches and end systems. These improved features will have different traffic characteristics than IPv4. The internet traffic which was earlier assumed as Poisson is now shown to have fractal characteristics as; heavy tailedness, self-similarity and long range dependency. Internet traffic showing above characteristics are found to have burstiness at multiple timescales. This behavior impacts network performance and degrades it substantially. It also increases complexity for network design and create difficulties to maintain desired QoS. IPv4 traffic has been well established as self-similar traffic. Nowadays, IPv6 forming a larger share of the internet traffic and it is pivotal to asses IPv6 with regards to fractal behavior. This will enable network designers to do necessary changes in the existing network to reconcile with IPv6. In this paper we compared IPv4 and IPv6 with respect to fractal behavioral characteristics. It is found that IPv6 shows higher degree of heavy tailedness, higher values of Hurst parameter values, higher fractal dimension values i.e. it is more self-similar, greater autocorrelation achieved even at larger lag and thus showing more burstiness.

Keywords


IPv4, IPv6, Self-Similarity, Long Range Dependence, Heavy Tailedness, Burstiness.

References